Computer Vision Lab, ETH Zurich, Switzerland

Augmented Perception Group

research at the confluence of

machine learning, computer vision,

and robotics

NEWS TEAM PUBLICATIONS

News

Team

The Augmented Perception research group was founded by Dr. Radu Timofte in the summer of 2016 as part of Computer Vision Laboratory, ETH Zurich led by Prof. Luc Van Gool.



The Augmented Perception Group mission is to explore new ways to equip machines with (super-)human perception capabilities and at the same time to augment the human perception using the developed algorithms and the computational power of the machines.


Group Leader: Dr. Radu Timofte

Radu Timofte

Radu Timofte is lecturer and research group leader in the Computer Vision Laboratory, at ETH Zurich, Switzerland. He obtained a PhD degree in Electrical Engineering at the KU Leuven, Belgium in 2013, the MSc at the Univ. of Eastern Finland in 2007, and the Dipl. Eng. at the Technical Univ. of Iasi, Romania in 2006. He serves as a reviewer for top journals (such as TPAMI, TIP, IJCV, TNNLS, TCSVT, CVIU, PR) and conferences (ICCV, CVPR, ECCV, NeurIPS) and is associate editor for top journals: Elsevier CVIU, IEEE Trans. PAMI , Elsevier Neurocomputing and SIAM Journal on Imaging Sciences. He serves(d) as area chair for ACCV 2018, ICCV 2019, ECCV 2020, ACCV 2020, CVPR 2021 and as Senior PC member for IJCAI 2019 and 2020. He received a NIPS 2017 best reviewer award. His work received the best student paper award at BMVC 2019, a best scientific paper award at ICPR 2012, the best paper award at CVVT workshop (ECCV 2012), the best paper award at ChaLearn LAP workshop (ICCV 2015), the best scientific poster award at EOS 2017, the honorable mention award at FG 2017, and his team won a number of challenges including traffic sign detection (IJCNN 2013), apparent age estimation (ICCV 2015) and real world super-resolution (ICCV 2019). He is co-founder of Merantix and co-organizer of NTIRE, CLIC, AIM and PIRM events. His current research interests include sparse and collaborative representations, deep learning, optical flow, image/video compression, restoration and enhancement.

Postdocs (co-supervision with Prof. Luc Van Gool )
  • Dr. Andres Romero, 8/2019-present,
  • Dr. Kai Zhang, 5/2019-present,
  • Dr. Martin Danelljan, 1/2019-present,
  • Dr. Zhiwu Huang, 10/2018-present,
  • Dr. Shuhang Gu, 1/2018-1/2020, assistant professor at University of Sydney,
  • Dr. Nikolay Kobyshev, 2018-2019, founder of Assaia,

PhD students (co-supervision with Prof. Luc Van Gool)
  • Prune Truong, 5/2020-
  • Ce Liu, 9/2019-present
  • Jingyun Liang, 9/2019-present
  • Evangelos Ntavelis, 5/2019-present
  • Goutam Bhat, 4/2019-present
  • Andreas Lugmayr, 2/2019-present
  • Ren Yang, 2/2019-present
  • Dario Fuoli, 1/2019-present
  • Ardhendu Shekhar Tripathi, 1/2019-present
  • Samarth Shukla, 6/2018-present
  • Christoph Mayer, 6/2018-present
  • Matthieu Paul, 6/2018-present
  • Yawei Li, 9/2017-present
  • Andrey Ignatov, 2017-present
  • Fabian Mentzer, 2017-present
  • Dr. Jiqing Wu, 2015-2017
  • Eirikur Agustsson, 2015-2018, now research scientist at Google
  • Dr. Till Kroeger, 2014-2018, now at Zoox
  • Irene Zarza, 2016
  • Joachim Curto, 2016
  • Dr. Rasmus Rothe, 2014-2016, founder of Merantix
  • Dr. Dengxin Dai, 2014-2016, now group leader in our Computer Vision Lab
Project staff
  • Florin Vasluianu, 10/2019-present
  • Dario Kneubuehler, 2/2019-12/2019
Guests
  • Anfeng He, 2019-2020, visiting PhD student from University of Science and Technology of China
Master & bachelor thesis projects
  • Richard von Moos, 4/2020-present
  • George-Cristian Cioflan, 4/2020-present
  • Philipp Andermatt, 2019-2020
  • Alexandre Carlier, 2019-2020
  • Xiaotang Du, 2019-2020
  • Marcel Buhler, 2019-2020
  • Kristofer Montazeri, 2019-2020
  • Gabriel Stalder, 2019
  • Julien Lamour, 2019
  • Manuel Fritsche, 2019
  • Kangning Liu, 2019, now PhD student at NYU
  • Berk Kaya, 2019, now PhD student in our Computer Vision Lab
  • Prune Truong, 2019, will join our group as PhD student starting 5/2020
  • Sohyeong Kim, 2019, now PhD student at EPFL
  • Francois Elvinger, 2019
  • Jingzhi Li, 2018-2019
  • Dario Fuoli, 2018-2019, now PhD student in our group
  • Andreas Steger, 2018, now PhD student in our group
  • Igor Susmelj, 2018
  • Etienne de Stoutz, 2018, bachelor thesis
  • Heiki Riesenkampf, 2018
  • Philippe Muller, 2017-2018
  • Asha Anoosheh, 2017-2018, now at Nnaisense
  • Alexander Sage, 2017, now at Nnaisense
  • Robert Torfason, 2017, now at Merantix
  • Fabian Mentzer, 2016-2017, now PhD student in our group
  • Andrey Ignatov, 2016-2017, now PhD student in our group
Master semester projects
  • Frederic Odermatt, 4/2020-present
  • Florin-Alexandru Vasluianu, 4/2020-present
  • Anastasia Sycheva, 5/2020-present
  • Yannick Strümpler, 2020
  • Steven Marty, 2020
  • Eric Marty, 2020
  • Joan Mihali, 2020
  • Silvio Paganucci, 2019-2020
  • Yang Xu, 2019-2020
  • Jelena Trisovic, 2019-2020
  • George-Cristian Cioflan, 2019-2020
  • Elias Rieder, 2019-2020
  • Simon Schaefer, 2019
  • Jakob Manz, 2019
  • Yufeng Zheng, 2019
  • Jingyuan Ma, 2019
  • Nicola Storni, 2019
  • Jagruti Patel, 2018-2019
  • Berk Kaya, 2018, now PhD student in our lab
  • Berk Dogan, 2018
  • Simon Benninger, 2018
  • Dejan Malesevic, 2018
  • Dario Panzuto, 2018
  • Joran Michiels, 2018
  • Yigit Baran Can, 2017-2018, now PhD student in our lab
  • Asha Anoosheh, 2017, now at NNaisense
  • Sveinn Palsson, 2017, now PhD student at DTU, Denmark
  • Igor Susmelj, 2017
  • Idil Kanpolat, 2017
  • Jonas Aeschbacher, 2017
  • Mahdi Hajibabaei, 2017
  • Andreas Steger, 2016-2017, now PhD student in our lab
  • Jianing Zhai, 2016
  • Robert Torfason, 2016, now at Merantix

Workshops and tutorials

We are co-organizing several workshops and tutorials, focused mainly on image and video restoration, enhancement, manipulation and compression. With these events we are aiming at providing a meeting place for the active people in each respective field and at promoting new research topics and new benchmarks. Below is a list of these events.

  • NTIRE: New Trends in Image Restoration and Enhancement workshop and associated challenges
    5 editions in conjunction with CVPR 2017 , 2018 , 2019 and 2020 and at ACCV 2016 .
  • CLIC: Workshop and Challenge on Image Compression

    3 editions in conjunction with CVPR 2018, 2019, 2020 .
  • AIM: Advances in Image Manipulation workshop and associated challenges

    in conjunction with ICCV 2019 and ECCV 2020
  • PIRM: Perceptual Image Restoration and Manipulation workshop and associated challenges

    in conjunction with ECCV 2018 .
  • FIRE: From Image Restoration to Enhancement and beyond tutorial

    in conjunction with ICCV 2019
  • Vision for All Seasons: Bad Weather and Nighttime workshop

    in conjunction with CVPR 2019

We are proud of the support of and the collaborations between the organizers, PC members, distinguished speakers, authors of published papers, challenge participants and winning teams.

Contact:

Radu Timofte, radu.timofte@vision.ee.ethz.ch

Computer Vision Laboratory

ETH Zurich, Switzerland

Collaborators




Publications


[171] Y. Li, W. Li, M. Danelljan, K. Zhang, S. Gu, L. Van Gool, R. Timofte. The Heterogeneity Hypothesis: Finding Layer-Wise Dissimilated Network Architecture. In arXiv preprint arXiv:2006.16242 , June 2020. [ bib |  pdf |  project page ]
 
[170] R. Yang, L. Van Gool, R. Timofte. OpenDVC: An Open Source Implementation of the DVC Video Compression Method. In arXiv preprint arXiv:2006.15862 , June 2020. [ bib |  pdf |  project page ]
 
[169] A. Lugmayr, M. Danelljan, L. Van Gool, R. Timofte. SRFlow: Learning the Super-Resolution Space with Normalizing Flow. In arXiv preprint arXiv:2006.14200 , June 2020. [ bib |  pdf |  project page ]
 
[168] R. Yang, F. Mentzer, L. Van Gool, R. Timofte. Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model. In arXiv preprint arXiv:2006.13560 , June 2020. [ bib |  pdf |  project page ]
 
[167] D. Kneubuehler, S. Gu, L. Van Gool, R. Timofte. Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network. In arXiv preprint arXiv:2005.06654 , May 2020. [ bib |  pdf |  project page (soon) ]
 
[166] M. Li, K. Zhang, W. Zuo, R. Timofte, D. Zhang. Learning Context-Based Non-local Entropy Modeling for Image Compression. In arXiv preprint arXiv:2005.04661 , May 2020. [ bib |  pdf |  project page (soon) ]
 
[165] F.K. Gustafsson, M. Danelljan, R. Timofte, T. B. Schön. How to Train Your Energy-Based Model for Regression. In arXiv preprint arXiv:2005.01698 , May 2020. [ bib |  pdf |  project page (soon) ]
 
[164] R. Yang, F. Mentzer, L. Van Gool, R. Timofte. Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2020. [ bib |  pdf |  project page ]
 
[163] Y. Li, S. Gu, C. Mayer, L. Van Gool, R. Timofte. Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2020. [ bib |  pdf |  project page (soon) ]
 
[162] B. Kaya, R. Timofte. Self-Supervised 2D Image to 3D Shape Translation with Disentangled Representations. In arXiv preprint arXiv:2003.10016 , March 2020. [ bib |  pdf |  project page (soon) ]
 
[161] K. Zhang, L. Van Gool, R. Timofte. Deep Unfolding Network for Image Super-Resolution. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2020. [ bib |  pdf |  project page (soon) ]
 
[160] G. Bhat, M. Danelljan, L. Van Gool, R. Timofte. Know Your Surroundings: Exploiting Scene Information for Object Tracking. In arXiv preprint arXiv:2003.11014 , March 2020. [ bib |  pdf |  project page (soon) ]
 
[159] G. Bhat, F.J. Lawin, M. Danelljan, A. Robinson, M. Felsberg, L. Van Gool, R. Timofte. Learning What to Learn for Video Object Segmentation. In arXiv preprint arXiv:2003.11540 , March 2020. [ bib |  pdf |  project page (soon) ]
 
[158] M. Danelljan, L. Van Gool, R. Timofte. Probabilistic Regression for Visual Tracking. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2020. [ bib |  pdf |  project page ]
 
[157] Y. Li, S. Gu, K. Zhang, L. Van Gool, R. Timofte. DHP: Differentiable Meta Pruning via HyperNetworks. In arXiv preprint arXiv:2003.13683 , March 2020. [ bib |  pdf |  project page ]
 
[156] M.C. Bühler, A. Romero, R. Timofte. DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution. In arXiv preprint arXiv:2004.04433 , April 2020. [ bib |  pdf |  project page (soon) ]
 
[155] E. Ntavelis, A. Romero, I. Kastanis, L. Van Gool, R. Timofte. SESAME: Semantic Editing of Scenes by Adding, Manipulating or Erasing Objects. In arXiv preprint arXiv:2004.04977 , April 2020. [ bib |  pdf |  project page (soon) ]
 
[154] K. Liu, S. Gu, A. Romero, R. Timofte. Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning. In arXiv preprint arXiv:2004.06502 , April 2020. [ bib |  pdf |  project page ]
 
[153] A. Abdelhamed, M. Afifi, R. Timofte, M.S. Brown et al. NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  SIDD+ dataset |  project page ]
 
[152] A. Lugmayr, M. Danelljan, R. Timofte et al. NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  supp. |  project page ]
 
[151] K. Zhang, S. Gu, R. Timofte et al. NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page ]
 
[150] D. Fuoli, Z. Huang, M. Danelljan, R. Timofte et al. NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page ]
 
[149] S. Yuan, R. Timofte, A. Leonardis, G. Slabaugh et al. NTIRE 2020 Challenge on Image Demoireing: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page ]
 
[148] B. Arad, R. Timofte, O. Ben-Shahar, Y.-T. Lin, G. Finlayson, S. Givati et al. NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page ]
 
[147] C.O. Ancuti, C. Ancuti, F.-A. Vasluianu, R. Timofte et al. NTIRE 2020 Challenge on NonHomogeneous Dehazing. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page ]
 
[146] C.O. Ancuti, C. Ancuti, R. Timofte. NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and Haze-Free Images. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page (soon) ]
 
[145] S. Nah, S. Son, R. Timofte, K.M. Lee et al. NTIRE 2020 Challenge on Image and Video Deblurring. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page ]
 
[144] A. Ignatov, J. Patel, R. Timofte. Rendering Natural Camera Bokeh Effect with Deep Learning. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page |  AIM 2020 challenge]
 
[] A. Ignatov, L. Van Gool, R. Timofte. Replacing Mobile Camera ISP with a Single Deep Learning Model. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2020. [ bib |  pdf |  project page ]
 
[143] A. Ignatov, L. Van Gool, R. Timofte. Replacing Mobile Camera ISP with a Single Deep Learning Model. In https://arxiv.org/abs/2002.05509 , February 2020. [ bib |  pdf |  project page ]
 
[142] M. Paul, C. Mayer, L. Van Gool, R. Timofte. Efficient Video Semantic Segmentation with Labels Propagation and Refinement. In 2020 Winter Conference on Applications of Computer Vision (WACV) , Aspen, CO, USA, March 2020. [ bib |  pdf ]
 
[88] C. Mayer, R. Timofte. Adversarial Sampling for Active Learning. In 2020 Winter Conference on Applications of Computer Vision (WACV) , Aspen, CO, USA, March 2020. [ bib |  pdf ]
 
[141] S. Gu, S. Guo, W. Zuo, Y. Chen, R. Timofte, L. Van Gool, L. Zhang. Learned Dynamic Guidance for Depth Image Reconstruction. In IEEE Trans Pattern Analysis and Machine Intelligence (TPAMI), December 2019. [ bib |  pdf |  Project page (soon)  ]
 
[] P. Truong, M. Danelljan, R. Timofte. GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2020. (oral) [ bib |  pdf |  project page (soon) ]
 
[140] P. Truong, M. Danelljan, R. Timofte. GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences. In https://arxiv.org/abs/1912.05524 , December 2019. [ bib |  pdf |  project page (soon) ]
 
[139] M. Fritsche, S. Gu, R. Timofte. Frequency Separation for Real-World Super-Resolution. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. (Winner of AIM challenge on real world image super-resolution) [ bib |  pdf |  project page ]
 
[138] A. Ignatov, R. Timofte, A. Kulik, S. Yang, K. Wang, F. Baum, M. Wu, L. Xu L. Van Gool. AI Benchmark: All About Deep Learning on Smartphones in 2019. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  project page ]
 
[137] C. Mayer, M. Paul, R. Timofte. Adversarial Feature Distribution Alignment for Semi-Supervised Learning. In arXiv preprint arXiv:1912.10428, December 2019. [ bib |  pdf |  project page (soon) ]
 
[136] Z Huang, D.P. Paudel, G. Li, J. Wu, R. Timofte, L. Van Gool. Divide-and-Conquer Adversarial Learning for High-Resolution Image and Video Enhancement. In arXiv preprint arXiv:1910.10455, December 2019. [ bib |  pdf |  project page (soon) ]
 
[135] C. Miron, V. Manta, R. Timofte, A. Pasarica, R.-I. Ciucu. Efficient convolutional neural network for apparent age prediction. In 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, Romania, 2019. [ bib |  pdf ]
 
[134] C. Miron, A. Pasarica, R.G.. Bozomitu, V. Manta, R. Timofte, R. Ciucu. Efficient Pupil Detection with a Convolutional Neural Network. In 2019 E-Health and Bioengineering Conference (EHB), Iasi, Romania, 2019. [ bib |  pdf ]
 
[133] C. Miron, A. Pasarica, H. Costin, V. Manta, R. Timofte, R. Ciucu. Hand Gesture Recognition based on SVM Classification. In 2019 E-Health and Bioengineering Conference (EHB), Iasi, Romania, 2019. [ bib |  pdf ]
 
[132] G.-C. Porusniuc, F. Leon, R. Timofte, C. Miron. Convolutional Neural Networks Architectures for Facial Expression Recognition. In 2019 E-Health and Bioengineering Conference (EHB), Iasi, Romania, 2019. [ bib |  pdf ]
 
[131] S. Nah, S. Son, R. Timofte, K.-M. Lee, et al. AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[130] A. Lugmayr, M. Danelljan, R. Timofte, M. Fritsche, S. Gu, et al. AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  project page (soon) |  challenge page ]
 
[129] S Gu, M Danelljan, R Timofte, et al. AIM 2019 Challenge on Image Extreme Super-Resolution: Methods and Results. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[128] S Gu, A Lugmayr, M Danelljan, M Fritsche, J Lamour, R Timofte. DIV8K: DIVerse 8K Resolution Image Dataset. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[127] S Shukla, L Van Gool, R Timofte. Extremely Weak Supervised Image-to-Image Translation for Semantic Segmentation. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  project page ]
 
[126] A Ignatov, J Patel, R Timofte, et al. AIM 2019 Challenge on Bokeh Effect Synthesis: Methods and Results. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[125] A Ignatov, R Timofte, et al. AIM 2019 Challenge on RAW to RGB Mapping: Methods and Results. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[124] K Zhang, S Gu, R Timofte, et al. AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[123] S Kim, G Li, D Fuoli, M Danelljan, Z Huang, S Gu, R Timofte. The Vid3oC and IntVID Datasets for Video Super Resolution and Quality Mapping. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[122] A. Lugmayr, M. Danelljan, R. Timofte. Unsupervised Learning for Real-World Super-Resolution. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[121] D. Fuoli, S. Gu, R. Timofte, et al. AIM 2019 Challenge on Video Extreme Super-Resolution: Methods and Results. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[120] D. Fuoli, S. Gu, R. Timofte, et al. Efficient Video Super-Resolution through Recurrent Latent Space Propagation. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  project page ]
 
[119] S. Yuan, R. Timofte, G. Slabaugh, A. Leonardis, et al. AIM 2019 Challenge on Image Demoireing: Methods and Results. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[118] S. Yuan, R. Timofte, G. Slabaugh, A. Leonardis. AIM 2019 Challenge on Image Demoireing: Dataset and Study. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  challenge page ]
 
[117] G. Bhat, M. Danelljan, L. Van Gool, R. Timofte. Learning Discriminative Model Prediction for Tracking. In The IEEE International Conference on Computer Vision (ICCV 2019) , Seoul, Korea, October 2019. (oral) [ bib |  pdf |  Project page ]
 
[116] Y. Li, S. Gu, L. Van Gool, R. Timofte. Learning Filter Basis for Convolutional Operations in Neural Networks. In The IEEE International Conference on Computer Vision (ICCV 2019) , Seoul, Korea, October 2019. [ bib |  pdf |  suppl |  Project page ]
 
[115] S. Gu, W. Li, L. Van Gool, R. Timofte. Fast Image Restoration Networks with Multi-bin Trainable Linear Unit. In The IEEE International Conference on Computer Vision (ICCV 2019) , Seoul, Korea, October 2019. [ bib |  pdf |  Project page ]
 
[114] S. Gu, Y. Li, L. Van Gool, R. Timofte. Self-Guided Network for Fast Image Denoising. In The IEEE International Conference on Computer Vision (ICCV 2019) , Seoul, Korea, October 2019. [ bib |  pdf |  Project page ]
 
[] E. Agustsson,M. Tschannen,F. Mentzer, R. Timofte, L. Van Gool. Generative Adversarial Networks for Extreme Learned Image Compression. In The IEEE International Conference on Computer Vision (ICCV 2019) , Seoul, Korea, October 2019. [ bib |  pdf |  suppl |  Project page ]
 
[113] A.S. Tripathi, M. Danelljan, L. Van Gool, R. Timofte. Tracking the Known and the Unknown by Leveraging Semantic Information. In 30th British Machine Vision Conference (BMVC 2019) , Cardiff, UK, September 2019. (oral) (Best Student Paper Award) [ bib |  pdf |  Project page ]
 
[112] C.O. Ancuti, C. Ancuti, M. Sbert, R. Timofte. Dense haze: A benchmark for image dehazing with dense-haze and haze-free images. In The IEEE International Conference on Image Processing (ICIP) , Taipei, Taiwan, September 2019. [ bib |  pdf |  Project page / dataset ]
 
[111] R. Patcas, R. Timofte, A. Volokitin, E. Agustsson, T. Eliades, M. Eichenberger, M.M. Bornstein. Facial attractiveness of cleft patients: a direct comparison between artificial-intelligence-based scoring and conventional rater groups. In European Journal of Orthodontics , February 2019. [ bib |  pdf ]
 
[110] B. Dogan, S. Gu, R. Timofte. Exemplar Guided Face Image Super-Resolution without Facial Landmarks. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , Long Beach, US, June 2019. [ bib |  pdf |  Project page ]
 
[109] S. Nah, R. Timofte, S. Gu, S. Baik, S. Hong, G. Moon, S. Son, K.M. Lee, et al. NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , Long Beach, US, June 2019. [ bib |  pdf |  Challenge page ]
 
[108] S. Nah, R. Timofte, S. Baik, S. Hong, G. Moon, S. Son, K.M. Lee, et al. Ntire 2019 challenge on video deblurring: Methods and results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019. [ bib |  pdf |  Challenge page ]
 
[107] S. Nah, S. Baik, S. Hong, G. Moon, S. Son, R. Timofte, K.M. Lee. NTIRE 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019. [ bib |  pdf |  Challenge page ]
 
[107] A. Abdelhamed, R. Timofte, M.S. Brown, et al. NTIRE 2019 challenge on real image denoising: Methods and results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019. [ bib |  pdf |  Challenge page ]
 
[106] S. Gu, R. Timofte, R. Zhang, et al. NTIRE 2019 challenge on image colorization: Report. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019. [ bib |  pdf |  Challenge page ]
 
[105] J. Cai, S. Gu, R. Timofte, L. Zhang, et al. NTIRE 2019 challenge on real image super-resolution: Methods and results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019. [ bib |  pdf |  Challenge page ]
 
[104] C.O. Ancuti, C. Ancuti, R. Timofte, L. Van Gool, L. Zhang, M.-H. Yang, et al. NTIRE 2019 Image Dehazing Challenge Report. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019. [ bib |  pdf |  Challenge page   Project page / dataset]
 
[103] A. Ignatov, R. Timofte, et al. NTIRE 2019 Challenge on Image Enhancement: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019. [ bib |  pdf |  Challenge page ]
 
[102] Y. Li, V. Tsiminaki, R. Timofte, M. Pollefeys, L. Van Gool. 3D Appearance Super-Resolution with Deep Learning. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2019. [ bib |  pdf |  suppl. material |  Project page  ]
 
[] E. Agustsson, A. Sage, R. Timofte, L. Van Gool. Optimal transport maps for distribution preserving operations on latent spaces of Generative Models. In International Conference on Learned Representations (ICLR) , New Orleans, US, May 2019. [ bib |  pdf ]
 
[101] S. Gu, R. Timofte. A brief review of image denoising algorithms and beyond. In Inpainting and Denoising Challenges. Springer series on Challenges in Machine Learning., 2019. [ bib |  pdf  ]
 
[100] D. Malesevic, C. Mayer, S. Gu, R. Timofte. Photo-realistic and Robust Inpainting of Faces using Refinement GANs. In Inpainting and Denoising Challenges. Springer series on Challenges in Machine Learning., 2019. [ bib |  pdf |  Project page (soon)  ]
 
[99] F. Mentzer, E. Agustsson, M. Tschannen, R. Timofte, L. Van Gool. Practical Full Resolution Learned Lossless Image Compression. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2019 (oral). [ bib |  pdf |  Project page |  Presentation  ]
 
[99] F. Mentzer, E. Agustsson, M. Tschannen, R. Timofte, L. Van Gool. Practical Full Resolution Learned Lossless Image Compression. In 1811.12817 , November 2018. [ bib |  pdf |  Project page  ]
 
[98] A. Romero, P. Arbelaez, L. Van Gool, R. Timofte. SMIT: Stochastic Multi-Label Image-to-Image Translation. In The IEEE International Conference on Computer Vision (ICCV) Workshops, October 2019. [ bib |  pdf |  Project page  ]
 
[98] A. Romero, P. Arbelaez, L. Van Gool, R. Timofte. SMIT: Stochastic Multi-Label Image-to-Image Translation. In 1812.03704 , December 2018. [ bib |  pdf |  Project page  ]
 
[ 97 ] B. Kaya, Y. B. Can, R. Timofte. Towards Spectral Estimation from a Single RGB Image in the Wild. In The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, Korea, October 2019. [ bib |  pdf |  Project page ]
 
[97] B. Kaya, Y. B. Can, R. Timofte. Towards Spectral Estimation from a Single RGB Image in the Wild. In 1812.00805 , December 2018. [ bib |  pdf |  Project page  ]
 
[96] A. Anoosheh, T. Sattler, R. Timofte, M. Pollefeys, L. Van Gool. Night-to-Day Image Translation for Retrieval-based Localization. In International Conference on Robotics and Automation (ICRA) , Montreal, Canada, May 2019. [ bib |  pdf |  Project page  ]
 
[96] A. Anoosheh, T. Sattler, R. Timofte, M. Pollefeys, L. Van Gool. Night-to-Day Image Translation for Retrieval-based Localization. In arXiv:1809.09767 , September 2018. [ bib |  pdf |  Project page  ]
 
[95] E. de Stoutz, A. Ignatov, N. Kobyshev, R. Timofte, L. Van Gool. Fast Perceptual Image Enhancement. In European Conference on Computer Vision (ECCV) Workshops , September 2018. [ bib |  pdf |  project page (soon) ]
 
[94] Y. Li, E. Agustsson, S. Gu, R. Timofte, L. Van Gool. CARN: Convolutional Anchored Regression Network for Fast and Accurate Single Image Super-Resolution. In European Conference on Computer Vision (ECCV) Workshops , September 2018. [ bib |  pdf |  code ]
 
[93] A. Ignatov, R. Timofte, et al. PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report. In European Conference on Computer Vision (ECCV) Workshops , September 2018. [ bib |  pdf |  arXiv ]  challenge page ]  PIRM workshop page ]
 
[92] A. Ignatov, R. Timofte, W. Chou, K. Wang, M. Wu, T. Hartley, L. Van Gool. AI Benchmark: Running Deep Neural Networks on Android Smartphones. In European Conference on Computer Vision (ECCV) Workshops , September 2018. [ bib |  pdf |  arXiv ]  AI Benchmark page ]
 
[91] Y. Blau, R. Mechrez, R. Timofte, T. Michaeli, L. Zelnik-Manor. The 2018 PIRM Challenge on Perceptual Image Super-resolution. In European Conference on Computer Vision (ECCV) Workshops , September 2018. [ bib |  pdf |  challenge page ]  PIRM workshop page ]
 
[90] M. Shoeiby, A. Robles-Kelly, R. Wei, R. Timofte. PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study. In European Conference on Computer Vision (ECCV) Workshops , September 2018. [ bib |  pdf |  challenge page ]  PIRM workshop page ]
 
[89] M. Shoeiby, A. Robles-Kelly, R. Timofte, R. Zhou, F. Lahoud, S. Susstrunk, Z. Xiong, Z. Shi, C. Chen, D. Liu, Z.-J. Zha, F. Wu, K. Wei, T. Zhang, L. Wang, Y. Fu, K. Nagasubramanian, A. K. Singh, A. Singh, S. Sarkar, B. Ganapathysubramanian. PIRM2018 Challenge on Spectral Image Super-Resolution: Methods and Results. In European Conference on Computer Vision (ECCV) Workshops , September 2018. [ bib |  pdf |  challenge page ]  PIRM workshop page ]
 
[88] C. Mayer, R. Timofte. Adversarial Sampling for Active Learning. In arXiv preprint arXiv:1808.06671, August 2018. [ bib |  pdf ]
 
[87] S. Gu, R. Timofte, and L. Van Gool. Integrating Local and Non-Local Denoiser Priors for Image Restoration. In 24th International Conference on Pattern Recognition (ICPR 2018), August 2018, China. [ bib | pdf ]
 
[86] C.O. Ancuti, C. Ancuti, R. Timofte, C. De Vleeschouwer. I-HAZE: a dehazing benchmark with real hazy and haze-free indoor images. In Advanced Concepts for Intelligent Vision Systems (ACIVS) , September 2018, France. [ bib |  pdf |  arXiv |  I-HAZE dataset ]  Challenge page ]
 
[85] C.O. Ancuti, C. Ancuti, R. Timofte, C. De Vleeschouwer. O-HAZE: a dehazing benchmark with real hazy and haze-free outdoor images. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2018. [ bib |  pdf |  O-HAZE dataset ]  Challenge page ]
 
[84] C. Mayer, R. Timofte, G. Paul. Towards Closing the Gap in Weakly Supervised Semantic Segmentation with DCNNs: Combining Local and Global Models. In arXiv preprint arXiv:1808.01625, July 2018. [ bib |  pdf ]
 
[83] S. Gu, R. Timofte, L. Van Gool. Multi-bin Trainable Linear Unit for Fast Image Restoration Networks In arXiv preprint arXiv:1807.11389 , July 2018. [ bib |  pdf ]
 
[82] R. Patcas, D.A.J. Bernini, A. Volokitin, E. Agustsson, R. Rothe, R. Timofte. Applying artificial intelligence to assess the impact of orthognathic treatment on facial attractiveness and estimated age. In International Journal of Oral and Maxillofacial Surgery , July 2018. [ bib |  pdf ]
 
[81] S. Palsson, E. Agustsson, R. Timofte, L. Van Gool. Generative Adversarial Style Transfer Networks for Face Aging. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2018. [ bib |  pdf ]
 
[80] R. Timofte, S. Gu, J. Wu, L. Van Gool, L. Zhang, M.-H. Yang, M. Harris, G. Shakhnarovich, N. Ukita, et al. NTIRE 2018 Challenge on Single Image Super-Resolution: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2018. [ bib |  pdf |  Challenge page ]
 
[79] C. Ancuti, C.O. Ancuti,R. Timofte, L. Van Gool, L. Zhang, M.-H. Yang, V.M. Patel, H. Zhang, V.A. Sindagi, et al. NTIRE 2018 Challenge on Image Dehazing: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2018. [ bib |  pdf |  Challenge page ]
 
[78] B. Arad, O. Ben-Shahar, R. Timofte, L. Van Gool, L. Zhang, M.-H. Yang, Z. Xiong, C. Chen, Z. Shi, D. Liu, F. Wu, et al. NTIRE 2018 Challenge on Spectral Reconstruction from RGB Images. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2018. [ bib |  pdf |  Challenge page ]
 
[77] Y.B. Can, R. Timofte. An efficient CNN for spectral reconstruction from RGB images. In arXiv:1804.04647, April 2018. [ bib |  pdf |  Project page ]
 
[76] E. Agustsson*, F. Mentzer*, M.  Tschannen*, R. Timofte, L. Van Gool. Generative Adversarial Networks for Extreme Learned Image Compression. In arXiv:1804.02958, April 2018. [ bib |  pdf |  Project page ](* equal contributions)
 
[75] E. Agustsson*, F. Mentzer*, M.  Tschannen, R. Timofte, L. Van Gool. Conditional Probability Models for Deep Image Compression. In Conference on Computer Vision and Pattern Recognition (CVPR), June 2018. [ bib |  pdf |  Project page (codes, data) ](* equal contributions)
 
[74] R. Torfason, F. Mentzer, E. Agustsson, M.  Tschannen, R. Timofte, L. Van Gool. Towards Image Understanding from Deep Compression without Decoding. In International Conference on Learning Representations (ICLR), April 2018. [ bib |  pdf ]
 
[73] A. Anoosheh, E. Agustsson, R. Timofte, L. Van Gool. ComboGAN: Unrestrained Scalability for Image Domain Translation. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2018. [ bib |  pdf |  Project page  ]
 
[73] A. Anoosheh, E. Agustsson, R. Timofte, L. Van Gool. ComboGAN: Unrestrained Scalability for Image Domain Translation. In 1712.06909, Dec 2017. [ bib |  pdf |  Project page  ]
 
[72] A. Sage, E. Agustsson, R. Timofte, L. Van Gool. Logo Synthesis and Manipulation with Clustered Generative Adversarial Networks. In Conference on Computer Vision and Pattern Recognition (CVPR), June 2018. [ bib |  pdf |  Source codes and LLD dataset (soon)  ]
 
[72] A. Sage, E. Agustsson, R. Timofte, L. Van Gool. Logo Synthesis and Manipulation with Clustered Generative Adversarial Networks. In 1712.04407, Dec 2017. [ bib |  pdf |  Source codes and LLD dataset (soon)  ]
 
[71] E. Agustsson, A. Sage, R. Timofte, L. Van Gool. Optimal transport maps for distribution preserving operations on latent spaces of Generative Models. In 1711.01970, Nov 2017. [ bib |  pdf ]
 
[70] A. Ignatov, N. Kobyshev, R. Timofte, K. Vanhoey, L. Van Gool. WESPE: Weakly Supervised Photo Enhancer for Digital Cameras. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2018. [ bib |  pdf |  Source codes and DPED dataset (soon) |  DEMO: phancer.com ]
 
[70] A. Ignatov, N. Kobyshev, R. Timofte, K. Vanhoey, L. Van Gool. WESPE: Weakly Supervised Photo Enhancer for Digital Cameras. In 1709.01118, Sept 2017. [ bib |  pdf |  Source codes and DPED dataset (soon) |  DEMO: phancer.com ]
 
[69] J. Aeschbacher, J. Wu, R. Timofte. In Defense of Shallow Learned Spectral Reconstruction from RGB Images. In IEEE International Conference on Computer Vision Workshop (ICCVW 2017), October 2017, Italy. [ bib |  pdf |  Source codes and data ]
 
[68] M. Hajibabaei, A. Volokitin, R. Timofte. Early Adaptation of Deep Priors in Age Prediction from Face Images. In IEEE International Conference on Computer Vision Workshop (ICCVW 2017), October 2017, Italy. [ bib |  pdf |  project page ]
 
[67] E. Agustsson, R. Timofte, L. Van Gool. Anchored Regression Networks applied to Age Estimation and Super Resolution. In International Conference on Computer Vision (ICCV 2017), October 2017, Italy. [ bib |  pdf ]
 
[66] I. Susmelj, E. Agustsson, R. Timofte. ABC-GAN: Adaptive Blur and Control for improved training stability of Generative Adversarial Networks. In International Conference on Machine Learning (ICML 2017) Workshop on Implicit Models, August 2017, Australia. [ bib |  pdf |  Workshop on Implicit Models |  models and codes ]
 
[65] E. Agustsson, R. Timofte. NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, July 2017. [ bib |  pdf |  NTIRE 2017 Workshop |  NTIRE 2017 SR Challenge factsheets |  NTIRE 2017 SR Challenge |  DIV2K dataset ]
 
[64] R. Timofte, E. Agustsson, L. Van Gool, M.-H. Yang, L. Zhang, B. Lim, S. Son, H. Kim, S. Nah, K.M. Lee, X. Wang, Y. Tian, K. Yu, Y. Zhang, S. Wu, C. Dong, L. Lin, Y. Qiao, C.C. Loy, W. Bae, J. Yoo, Y. Han, J.C. Ye, J.-S. Choi, M. Kim, Y. Fan, J. Yu, W. Han, D. Liu, H. Yu, Z. Wang, H. Shi, X. Wang, T.S. Huang, Y. Chen, K. Zhang, W. Zuo, Z. Tang, L. Luo, S. Li, M. Fu, L. Cao, W. Heng, G. Bui, T. Le, Y. Duan, D. Tao, R. Wang, X. Lin, J. Pang, J. Xu, Y. Zhao, X. Xu, J. Pan, D. Sun, Y. Zhang, X. Song, Y. Dai, X. Qin, X.-P. Huynh, T. Guo, H.S. Mousavi, T.H. Vu, V. Monga, C. Cruz, K. Egiazarian, V. Katkovnik, R. Mehta, A.K. Jain, A. Agarwalla, C.V.S. Praveen, R. Zhou, H. Wen, C. Zhu, Z. Xia, Z. Wang, Q. Guo. NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, July 2017. [ bib |  pdf |  NTIRE 2017 Workshop |  NTIRE 2017 SR Challenge factsheets |  NTIRE 2017 SR Challenge |  DIV2K dataset |  suppl. results ]
 
[63] D. Bernini-Hodel, E. Agustsson, R. Timofte, S. Affolter, R. Patcas. Using artificial intelligence to evaluate the impact of orthognathic therapy on apparent age and facial attractiveness. In The 93rd European Orthodontic Society Congress (EOS 2017), June 2017, Switzerland. (Best Scientific Poster Award) [ bib |  pdf |  poster ]
 
[62] E. Agustsson, F. Mentzer, M. Tschannen, L. Cavigelli, R. Timofte, L. Benini, L. Van Gool. Soft-to-Hard Vector Quantization for End-to-End Learned Compression of Images and Neural Networks. In 2017 Conference on Neural Information Processing Systems (NIPS) , April 2017. [ bib |  pdf ]
 
[62] E. Agustsson, F. Mentzer, M. Tschannen, L. Cavigelli, R. Timofte, L. Benini, L. Van Gool. Soft-to-Hard Vector Quantization for End-to-End Learned Compression of Images and Neural Networks. In 1704.00648, April 2017. [ bib |  pdf ]
 
[61] Y. Liang, R. Timofte, J. Wang, Y. Gong, N. Zheng. Single Image Super Resolution-When Model Adaptation Matters. In 1703.10889, March 2017. [ bib |  pdf |  Source codes and data (soon) ]
 
[60] J. Wu, R. Timofte, Z. Huang, L. Van Gool. On the Relation between Color Image Denoising and Classification. In 1704.01372, April 2017. [ bib |  pdf |  Source codes and data (soon) ]
 
[59] A. Ignatov, N. Kobyshev, R. Timofte, K. Vanhoey, L. Van Gool. DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks. In International Conference on Computer Vision (ICCV 2017), October 2017, Italy. [ bib |  pdf |  suppl. mat. |  Source codes and DPED dataset |  DEMO: phancer.com ]
 
[59] A. Ignatov, N. Kobyshev, R. Timofte, K. Vanhoey, L. Van Gool. DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks. In 1704.02470, April 2017. [ bib |  pdf |  Source codes and DPED dataset |  DEMO: phancer.com ]
 
[58] J. Kwon, R. Timofte, and L. Van Gool. Leveraging observation uncertainty for robust visual tracking. Journal Computer Vision and Image Understanding (CVIU 2017), 2017. [ bib |  pdf ]
 
[57] E. Agustsson, R. Timofte, S. Escalera, X. Baro, I. Guyon, and R. Rothe, Apparent and real age estimation in still images with deep residual regressors on APPA-REAL database. In 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), May 2017, US. (Honorable Mention Award) [ bib | pdf |APPA-REAL database ]
 
[56] A. Steger and R. Timofte. Failure Detection for Facial Landmark Detectors. In 13th Asian Conference on Computer Vision (ACCV Workshops 2016), November 2016, Taiwan. [ bib | pdf ]
 
[55] J. Wu, R. Timofte, and L. Van Gool. Generic 3D Convolutional Fusion for Image Restoration. In 13th Asian Conference on Computer Vision (ACCV Workshops 2016), November 2016, Taiwan. [ bib | pdf ]
 
[54] R. Torfason, E. Agustsson, R. Rothe, and R. Timofte. From face images and attributes to attributes. In 13th Asian Conference on Computer Vision (ACCV 2016), November 2016, Taiwan. [ bib | pdf ]
 
[53] R. Rothe, R. Timofte, and L. Van Gool. Deep expectation of real and apparent age from a single image without facial landmarks. Journal International Journal of Computer Vision (IJCV 2016), 2016. [ bib |  pdf |  Models and IMDB-WIKI dataset |  DEMO: howhot.io ]
 
[52] R. Timofte. Anchored Fusion for Image Restoration. In 23rd International Conference on Pattern Recognition (ICPR 2016), December 2016, Mexico. [ bib | pdf |  Source codes and images (soon) ]
 
[51] E. Agustsson, R. Timofte, and L. Van Gool. Regressor Basis Learning for Anchored Super-Resolution. In 23rd International Conference on Pattern Recognition (ICPR 2016), December 2016, Mexico. [ bib | pdf ]
 
[50] E. Agustsson, R. Timofte, and L. Van Gool. k2-means for fast and accurate large scale clustering. In The European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), September 2017, Macedonia. [ bib |  pdf]
 
[50] E. Agustsson, R. Timofte, and L. Van Gool. k2-means for fast and accurate large scale clustering. In arXiv:1605.09299, May 2016. [ bib |  pdf |  Source codes and data (soon) ]
 
[49] J. Wu, R. Timofte, and L. Van Gool. Demosaicing based on Directional Difference Regression and Efficient Regression Priors. Journal IEEE Transactions on Image Processing (TIP 2016), 2016. [ bib |  pdf |  Source codes and images ]
 
[48] A. Volokitin, R. Timofte, and L. Van Gool. Deep Features or Not: Temperature and Time Prediction in Outdoor Scenes. In Robust Features for Computer Vision workshop (CVPR 2016), June 2016, US. [ bib |  pdf |  Source codes and images ]
 
[47] M. Uricar, R. Timofte, R. Rothe, J. Matas, and L. Van Gool. Structured Output SVM Prediction of Apparent Age, Gender and Smile From Deep Features. In ChaLearn Looking at People and Faces of the World: Face Analysis Workshop and Challenge (CVPR 2016), June 2016, US. (3rd place of LAP challenge on apparent age estimation) [ bib |  pdf |  Source codes and models ]
 
[46] T. Kroeger, R. Timofte, D. Dai, and L. Van Gool. Fast Optical Flow using Dense Inverse Search. In European Conference on Computer Vision (ECCV 2016), October 2016, Netherlands. [ bib |  pdf |  Project page ]
 
[46] T. Kroeger, R. Timofte, D. Dai, and L. Van Gool. Fast Optical Flow using Dense Inverse Search. In arXiv:1603.03590, March 2016. [ bib |  pdf |  Project page ]
 
[45] R. Timofte, J. Kwon, and L. Van Gool. PICASO: PIxel Correspondences And SOft Match Selection for Real-time Tracking. Journal Computer Vision and Image Understanding (CVIU 2016), 2016. [ bib |  pdf |  Project page ]
 
[44] S. Manen, R. Timofte, D. Dai, and L. Van Gool. Leveraging single for multi-target tracking using a novel trajectory overlap affinity measure. In IEEE Winter Conference on Applications of Computer Vision (WACV 2016), March 2016, US. [ bib |  pdf |  Suppl. material ]
 
[43] R. Timofte, R. Rothe, and L. Van Gool. Seven ways to improve example-based single image super resolution. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2016), June 2016, US. [ bib |  pdf |  Supplementary material |  L20 dataset ]
 
[43] R. Timofte, R. Rothe, and L. Van Gool. Seven ways to improve example-based single image super resolution. In arXiv:1511.02228, November 2015. [ bib |  pdf ]
 
[42] R. Rothe, R. Timofte, and L. Van Gool. Some like it hot - visual guidance for preference prediction. In 2016 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2016), June 2016, US. [ bib |  pdf |  DEMO: howhot.io ]
 
[42] R. Rothe, R. Timofte, and L. Van Gool. Some like it hot - visual guidance for preference prediction. In arXiv:1510.07867, October 2015. [ bib |  pdf |  DEMO: howhot.io ]
 
[41] R. Rothe, R. Timofte, and L. Van Gool. DEX: Deep EXpectation of apparent age from a single image. In Looking at People Workshop at International Conference on Computer Vision (ICCV 2015), December 2015, Chile. (Winner of LAP challenge on apparent age estimation) (NVIDIA ChaLearn LAP 2015 Best Paper Award) [ bib |  pdf |  Models and IMDB-WIKI dataset |  DEMO: howhot.io ]
 
[40] R. Rothe, R. Timofte, and L. Van Gool. DLDR: Deep Linear Discriminative Retrieval for cultural event classification from a single image. In Looking at People Workshop at International Conference on Computer Vision (ICCV 2015), December 2015, Chile. (Top entry in LAP challenge on cultural event recognition) [ bib |  pdf ]
 
[39] R. Timofte*, V. De Smet*, and L. Van Gool. Semantic super-resolution: when and where is it useful? Journal Computer Vision and Image Understanding (CVIU 2015), 2015. (* equal contributions) [ bib |  pdf ]
 
[38] R. Rothe, R. Timofte, and L. Van Gool. Efficient Regression Priors for Reducing Image Compression Artifacts. In 22nd IEEE International Conference on Image Processing (ICIP 2015), September 2015, Canada. [ bib |  pdf |  Source codes and images ]
 
[37] J. Wu, R. Timofte, and L. Van Gool. Efficient Regression Priors for Post-processing Demosaiced Images. In 22nd IEEE International Conference on Image Processing (ICIP 2015), September 2015, Canada. [ bib |  pdf |  Source codes and images (soon) ]
 
[36] H. Honda, R. Timofte, and L. Van Gool. Make My Day - High-Fidelity Color Denoising with Near-Infrared. In 11th IEEE Workshop on Perception Beyond the Visible Spectrum (PBVS) - CVPR Workshops, June 2015, USA. [ bib |  pdf |   MMD images (RGB+NIR) ]
 
[35] D. Dai, T. Kroeger, R. Timofte, and L. Van Gool. Metric Imitation by manifold transfer for efficient vision applications. In 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2015), June 2015, USA. [ bib |  pdf |  Project ]
 
[34] D. Dai, R. Timofte, and L. Van Gool. Jointly Optimized Regressors for Image Super-resolution. Journal Computer Graphics Forum, vol. 34, num. 2, pp. 95-104, June 2015. [ bib |  pdf |  Source codes ]
 
[34] D. Dai, R. Timofte, and L. Van Gool. Jointly Optimized Regressors for Image Super-resolution. In The 36th Annual Conference of the European Association for Computer Graphics (EUROGRAPHICS 2015), May 2015, Switzerland. [ bib |  pdf |  Source codes ]
 
[33] R. Timofte and L. Van Gool. SparseFlow: Sparse Matching for Small to Large Displacement Optical Flow. In IEEE Winter Conference on Applications of Computer Vision (WACV 2015), January 2015, US. [ bib |  pdf |  Source codes ]
 
[32] J. Wu, R. Timofte, and L. Van Gool. Learned Collaborative Representations for Image Classification. In IEEE Winter Conference on Applications of Computer Vision (WACV 2015), January 2015, US. [ bib |  pdf |  Source codes ]
 
[31] T. Kroeger, D. Dai, R. Timofte, and L. Van Gool. Discovery of Sets of Mutually Orthogonal Vanishing Points in Videos. In 1st Workshop on Benchmarking multi-target tracking (BMTT @ WACV 2015), January 2015, US. [ bib |  pdf | more ]
 
[30] R. Timofte, V. De Smet, and L. Van Gool. A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution. In Asian Conference on Computer Vision (ACCV 2014), November 2014, Singapore. [ bib |  pdf |  Supplementary material |  Source codes ]
 
[29] R. Timofte and L. Van Gool. Iterative Nearest Neighbors. Journal Pattern Recognition (PR 2014), 2014. [ bib |  pdf |  Source codes ]
 
[28] M. Pedersoli, R. Timofte, T. Tuytelaars, and L. Van Gool. An Elastic Deformation Field Model for Object Detection and Tracking. In International Journal of Computer Vision, June 2014. [ bib |  pdf ]
 
[27] M. Pedersoli, R. Timofte, T. Tuytelaars, and L. Van Gool. An Elastic Deformation Field Model for Object Detection and Tracking. In Tech. Report, KU Leuven/ESAT/PSI/1402, April 2014, Belgium. [ bib |  pdf ]
 
[26] B. Verhagen, R. Timofte, and L. Van Gool. Scale-Invariant Line Descriptors for Wide Baseline Matching. In Winter Conference on Applications of Computer Vision (WACV 2014), March 2014, USA. [ bib |  pdf |  Source codes ]
 
[25] R. Timofte, V. De Smet, and L. Van Gool. Anchored Neighborhood Regression for Fast Example-Based Super-Resolution. In International Conference on Computer Vision (ICCV 2013), December 2013, Australia. [ bib |  pdf |  poster |  Supplementary material |  Source codes ]
 
[24] M. Mathias, R. Benenson, R. Timofte, and L. Van Gool. Handling Occlusions with Franken-classifiers. In International Conference on Computer Vision (ICCV 2013), December 2013, Australia. [ bib | pdf (includes supplementary material) ]
 
[23] R. Timofte and L. Van Gool. Adaptive and Weighted Collaborative Representations for Image Classification. Journal Pattern Recognition Letters (PRL 2014), vol.43, July 2014. [ bib | pdf |  Source codes ]
 
[22] F.  Schouwenaars, R. Timofte, and L. Van Gool. Robust Scene Stitching in Large Scale Mobile Mapping. In British Machine Vision Conference (BMVC 2013), September 2013, UK. [ bib | pdf ]
 
[21] R. Timofte. Sparse and Collaborative Representations for Computer Vision. PhD Thesis (supervisor: Prof. Dr. Ing. Luc Van Gool), KU Leuven, June 2013, Belgium. [ bib | pdf ]
 
[20] R. Timofte, and L. Van Gool. Efficient Loopy Belief Propagation using the Four Color Theorem. In Advanced Topics in Computer Vision, Series Title: Advances in Computer Vision and Pattern Recognition . Editors: G. Farinella, S. Battiato, and R. Cipolla. Springer-Verlag London Ltd., 2013. (in print) [ bib | pdf ]
 
[19] M.  Mathias*, R. Timofte*, R. Benenson, and L. Van Gool. Traffic Sign Recognition - How far are we from the solution?. In International Joint Conference on Neural Networks (IJCNN 2013), August 2013, Dallas, USA. (* equal contributions) (Winner of GTSDB challenge on traffic sign detection) (Third entry of GTSRB challenge on traffic sign classification) [ bib |  html | pdf ]
 
[18] R. Timofte and L. Van Gool. Weighted Collaborative Representation and Classification of Images. In 21st International Conference on Pattern Recognition (ICPR 2012), November 2012, Japan. (Best Scientific Paper Award) [ bib | pdf ]
 
[17] R. Timofte, T. Tuytelaars, and L. Van Gool. Naive Bayes Image Classification: beyond Nearest Neighbors. In Asian Conference on Computer Vision (ACCV 2012), November 2012, Korea. [ bib | pdf ]
 
[16] R. Timofte and L. Van Gool. Automatic Stave Discovery for Musical Facsimiles. In Asian Conference on Computer Vision (ACCV 2012), November 2012, Korea. [ bib |  Supplementary material | pdf ]
 
[15] R. Benenson, M. Mathias, R. Timofte, and L. Van Gool. Fast Stixel Computation for Fast Pedestrian Detection. In 3rd IEEE Workshop on Computer Vision in Vehicle Technology: From Earth to Mars (CVVT @ ECCV 2012), October 2012, Italy. (Best Paper Award) [ bib | pdf | more ]
 
[14] B. Gunyel, R. Benenson, R. Timofte, and L. Van Gool. Stixels Motion Estimation without Optical Flow Computation. In 12th European Conference on Computer Vision (ECCV 2012), October 2012, Italy. [ bib | pdf | more ]
 
[13] R. Timofte and L. Van Gool. A Training-free Classification Framework for Textures, Writers, and Materials. In British Machine Vision Conference (BMVC 2012), September 2012, UK. [ bib | pdf ]
 
[12] R. Timofte and L. Van Gool. Iterative Nearest Neighbors for Classification and Dimensionality Reduction. In 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2012), June 2012, USA. [ bib | pdf | INNC.m ]
 
[11] R. Benenson, M. Mathias, R. Timofte, and L. Van Gool. Pedestrian Detection at 100 Frames per Second. In 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2012), June 2012, USA. [ bib | pdf | more ]
 
[10] R. Timofte, K. Zimmermann, and L. Van Gool. Multi-view Traffic Sign Detection, Recognition, and 3D Localisation. Journal of Machine Vision and Applications (MVA 2011), DOI 10.1007/s00138-011-0391-3, December 2011, Springer-Verlag. [ bib |  html | pdf ]
 
[9] V. Lasdas, R. Timofte, and L. Van Gool. Non-Parametric Motion-Priors for Flow Understanding. In IEEE Workshop on Applications of Computer Vision (WACV 2012), January 2012, USA. [ bib |  children_sequence.zip | pdf ]
 
[8] R. Timofte, V.A. Prisacariu, L.J. Van Gool, and I. Reid. Combining Traffic Sign Detection with 3D Tracking Towards Better Driver Assistance. Emerging Topics in Computer Vision and its Applications (editor: C.H. Chen). World Scientific Publishing. September 2011. [ bib |  html | pdf ]
 
[7] R. Timofte and L. Van Gool. Multi-view Manhole Detection, Recognition, and 3D Localisation. In 1st IEEE/ISPRS Workshop on Computer Vision for Remote Sensing of the Environment (CVRS @ ICCV 2011), November 2011, Barcelona, Spain. [ bib | pdf ]
 
[6] R. Benenson, R. Timofte, and L. Van Gool. Stixels Estimation Without Depth Map Computation. In 2nd IEEE Workshop on Computer Vision in Vehicle Technology: From Earth to Mars (CVVT @ ICCV 2011), November 2011, Barcelona, Spain. [ bib | pdf | more ]
 
[5] R. Timofte and L. Van Gool. Sparse Representation Based Projections. In British Machine Vision Conference (BMVC 2011), 2011, UK. [ bib | pdf ]
 
[4] R. Timofte and L. Van Gool. Four Colour Theorem for Fast Early Vision. In Asian Conference on Computer Vision (ACCV 2010), November 2010, New Zealand. [ bib |  Supplementary material | pdf ]
 
[3] J. Knopp, M. Prasad, G. Willems, R. Timofte and L. Van Gool. Hough Transform and 3D SURF for Robust Three Dimensional Classification. In European Conference on Computer Vision (ECCV 2010), September 2010, Greece. [ bib |  html | pdf ]
 
[2] V.A. Prisacariu, R. Timofte, K. Zimmermann, I. Reid, and L. Van Gool. Integrating Object Detection with 3D Tracking Towards a Better Driver Assistance System. In International Conference on Pattern Recognition (ICPR 2010), August 2010, Turkey. [ bib |  html | pdf ]
 
[1] R. Timofte, K. Zimmermann, and L. Van Gool. Multi-view Traffic Sign Detection, Recognition, and 3D Localisation. In IEEE Workshop on Applications of Computer Vision (WACV 2009), December 2009, USA. [ bib |  html | pdf ]
 
Latest change 16:58 2020/07/05
Contact:

Dr. Radu Timofte, radu.timofte@vision.ee.ethz.ch

Computer Vision Laboratory, ETH Zurich

Sternwartstrasse 7, ETH Zentrum, CH - 8092 Zurich, Switzerland

Office: ETF C107

Tel: +41 44 63 25279 Fax: +41 44 63 21199