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ORCIDLuc Van Gool
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- affiliation: ETH Zurich, Computer Vision Lab
- affiliation: KU Leuven, Center for Processing Speech and Images (PSI-VISICS)
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2020 – today
- 2020
[j145]Dengxin Dai
, Christos Sakaridis, Simon Hecker, Luc Van Gool:
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding. Int. J. Comput. Vis. 128(5): 1182-1204 (2020)- [j144]Li Liu, Matti Pietikäinen, Jie Qin, Wanli Ouyang, Luc Van Gool:
Efficient Visual Recognition. Int. J. Comput. Vis. 128(8): 1997-2001 (2020) - [j143]Shuhang Gu, Shi Guo, Wangmeng Zuo, Yunjin Chen, Radu Timofte, Luc Van Gool, Lei Zhang:
Learned Dynamic Guidance for Depth Image Reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 42(10): 2437-2452 (2020) - [j142]Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Geometrically Mappable Image Features. IEEE Robotics Autom. Lett. 5(2): 2062-2069 (2020) - [j141]Vaishakh Patil, Wouter Van Gansbeke, Dengxin Dai, Luc Van Gool:
Don't Forget The Past: Recurrent Depth Estimation from Monocular Video. IEEE Robotics Autom. Lett. 5(4): 6813-6820 (2020) - [j140]Mengshi Qi, Yunhong Wang, Jie Qin, Annan Li, Jiebo Luo, Luc Van Gool:
stagNet: An Attentive Semantic RNN for Group Activity and Individual Action Recognition. IEEE Trans. Circuits Syst. Video Technol. 30(2): 549-565 (2020) - [c618]Despoina Paschalidou, Luc Van Gool, Andreas Geiger:
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects From a Single RGB Image. CVPR 2020: 1057-1067 - [c617]Anna Volokitin, Ender Konukoglu, Luc Van Gool:
Decomposing Image Generation into Layout Prediction and Conditional Synthesis. CVPR Workshops 2020: 1530-1538 - [c616]Andrey Ignatov, Luc Van Gool, Radu Timofte:
Replacing Mobile Camera ISP with a Single Deep Learning Model. CVPR Workshops 2020: 2275-2285 - [c615]Kai Zhang, Luc Van Gool, Radu Timofte:
Deep Unfolding Network for Image Super-Resolution. CVPR 2020: 3214-3223 - [c614]Suman Saha, Wenhao Xu, Menelaos Kanakis, Stamatios Georgoulis, Yuhua Chen, Danda Pani Paudel, Luc Van Gool:
Domain Agnostic Feature Learning for Image and Video Based Face Anti-spoofing. CVPR Workshops 2020: 3490-3499 - [c613]Qi Dai, Vaishakh Patil, Simon Hecker, Dengxin Dai, Luc Van Gool, Konrad Schindler:
Self-supervised Object Motion and Depth Estimation from Video. CVPR Workshops 2020: 4326-4334 - [c612]Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte:
Learning for Video Compression With Hierarchical Quality and Recurrent Enhancement. CVPR 2020: 6627-6636 - [c611]Fabian Mentzer, Luc Van Gool, Michael Tschannen:
Learning Better Lossless Compression Using Lossy Compression. CVPR 2020: 6637-6646 - [c610]Martin Danelljan, Luc Van Gool, Radu Timofte:
Probabilistic Regression for Visual Tracking. CVPR 2020: 7181-7190 - [c609]Yawei Li, Shuhang Gu, Christoph Mayer, Luc Van Gool, Radu Timofte:
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR 2020: 8015-8024 - [c608]Chengde Wan, Thomas Probst, Luc Van Gool, Angela Yao:
Dual Grid Net: Hand Mesh Vertex Regression from Single Depth Maps. ECCV (30) 2020: 442-459 - [c607]Anna Volokitin, Ertunc Erdil, Neerav Karani, Kerem Can Tezcan, Xiaoran Chen, Luc Van Gool, Ender Konukoglu:
Modelling the Distribution of 3D Brain MRI Using a 2D Slice VAE. MICCAI (7) 2020: 657-666 - [c606]Evangelos Ntavelis, Iason Kastanis, Luc Van Gool, Radu Timofte:
Same Same but Different: Augmentation of Tiny Industrial Datasets using Generative Adversarial Networks. SDS 2020: 17-22 - [c605]Zhicheng Fang, Xiaoran Chen, Yuhua Chen, Luc Van Gool:
Towards Good Practice for CNN-Based Monocular Depth Estimation. WACV 2020: 1080-1089 - [c604]Matthieu Paul, Christoph Mayer, Luc Van Gool, Radu Timofte:
Efficient Video Semantic Segmentation with Labels Propagation and Refinement. WACV 2020: 2862-2871 - [i215]Vaishakh Patil, Wouter Van Gansbeke, Dengxin Dai, Luc Van Gool:
Don't Forget The Past: Recurrent Depth Estimation from Monocular Video. CoRR abs/2001.02613 (2020) - [i214]Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool:
MTI-Net: Multi-Scale Task Interaction Networks for Multi-Task Learning. CoRR abs/2001.06902 (2020) - [i213]Andrey Ignatov, Luc Van Gool, Radu Timofte:
Replacing Mobile Camera ISP with a Single Deep Learning Model. CoRR abs/2002.05509 (2020) - [i212]Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte:
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement. CoRR abs/2003.01966 (2020) - [i211]Arun Balajee Vasudevan, Dengxin Dai, Luc Van Gool:
Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds. CoRR abs/2003.04210 (2020) - [i210]Clara Fernandez-Labrador, Ajad Chhatkuli, Danda Pani Paudel, José Jesús Guerrero, Cédric Demonceaux, Luc Van Gool:
Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets. CoRR abs/2003.07619 (2020) - [i209]Yawei Li, Shuhang Gu, Christoph Mayer, Luc Van Gool, Radu Timofte:
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CoRR abs/2003.08935 (2020) - [i208]Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Geometrically Mappable Image Features. CoRR abs/2003.09682 (2020) - [i207]Fabian Mentzer, Luc Van Gool, Michael Tschannen:
Learning Better Lossless Compression Using Lossy Compression. CoRR abs/2003.10184 (2020) - [i206]Kai Zhang, Luc Van Gool, Radu Timofte:
Deep Unfolding Network for Image Super-Resolution. CoRR abs/2003.10428 (2020) - [i205]Goutam Bhat, Martin Danelljan, Luc Van Gool, Radu Timofte:
Know Your Surroundings: Exploiting Scene Information for Object Tracking. CoRR abs/2003.11014 (2020) - [i204]Goutam Bhat, Felix Järemo Lawin, Martin Danelljan, Andreas Robinson, Michael Felsberg, Luc Van Gool, Radu Timofte:
Learning What to Learn for Video Object Segmentation. CoRR abs/2003.11540 (2020) - [i203]Martin Danelljan, Luc Van Gool, Radu Timofte:
Probabilistic Regression for Visual Tracking. CoRR abs/2003.12565 (2020) - [i202]Yawei Li, Shuhang Gu, Kai Zhang, Luc Van Gool, Radu Timofte:
DHP: Differentiable Meta Pruning via HyperNetworks. CoRR abs/2003.13683 (2020) - [i201]Despoina Paschalidou, Luc Van Gool, Andreas Geiger:
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image. CoRR abs/2004.01176 (2020) - [i200]Martin Hahner, Dengxin Dai, Alexander Liniger, Luc Van Gool:
Quantifying Data Augmentation for LiDAR based 3D Object Detection. CoRR abs/2004.01643 (2020) - [i199]Evangelos Ntavelis, Andrés Romero, Iason Kastanis, Luc Van Gool, Radu Timofte:
SESAME: Semantic Editing of Scenes by Adding, Manipulating or Erasing Objects. CoRR abs/2004.04977 (2020) - [i198]Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, Dengxin Dai, Luc Van Gool:
Revisiting Multi-Task Learning in the Deep Learning Era. CoRR abs/2004.13379 (2020) - [i197]Jan-Nico Zaech, Dengxin Dai, Alexander Liniger, Luc Van Gool:
Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Context. CoRR abs/2004.14251 (2020) - [i196]Dario Kneubuehler, Shuhang Gu, Luc Van Gool, Radu Timofte:
Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network. CoRR abs/2005.06654 (2020) - [i195]Alexander Liniger, Luc Van Gool:
Safe Motion Planning for Autonomous Driving using an Adversarial Road Model. CoRR abs/2005.07691 (2020) - [i194]Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, Luc Van Gool:
Learning To Classify Images Without Labels. CoRR abs/2005.12320 (2020) - [i193]Christos Sakaridis, Dengxin Dai, Luc Van Gool:
Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation. CoRR abs/2005.14553 (2020) - [i192]Suryansh Kumar, Luc Van Gool, Carlos E. P. de Oliveira, Anoop Cherian, Yuchao Dai, Hongdong Li:
Dense Non-Rigid Structure from Motion: A Manifold Viewpoint. CoRR abs/2006.09197 (2020) - [i191]Yuhua Chen, Luc Van Gool, Cordelia Schmid, Cristian Sminchisescu:
Consistency Guided Scene Flow Estimation. CoRR abs/2006.11242 (2020) - [i190]Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte:
Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model. CoRR abs/2006.13560 (2020) - [i189]Andreas Lugmayr, Martin Danelljan, Luc Van Gool, Radu Timofte:
SRFlow: Learning the Super-Resolution Space with Normalizing Flow. CoRR abs/2006.14200 (2020) - [i188]Rui Gong, Dengxin Dai, Yuhua Chen, Wen Li, Luc Van Gool:
Analogical Image Translation for Fog Generation. CoRR abs/2006.15618 (2020) - [i187]Ren Yang, Luc Van Gool, Radu Timofte:
OpenDVC: An Open Source Implementation of the DVC Video Compression Method. CoRR abs/2006.15862 (2020) - [i186]Yawei Li, Wen Li, Martin Danelljan, Kai Zhang, Shuhang Gu, Luc Van Gool, Radu Timofte:
The Heterogeneity Hypothesis: Finding Layer-Wise Dissimilated Network Architecture. CoRR abs/2006.16242 (2020) - [i185]Guolei Sun, Wenguan Wang, Jifeng Dai, Luc Van Gool:
Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation. CoRR abs/2007.01947 (2020) - [i184]Rui Gong, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Self-Calibration Supported Robust Projective Structure-from-Motion. CoRR abs/2007.02045 (2020) - [i183]Anna Volokitin, Ertunc Erdil, Neerav Karani, Kerem Can Tezcan, Xiaoran Chen, Luc Van Gool, Ender Konukoglu:
Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE. CoRR abs/2007.04780 (2020) - [i182]Anton Obukhov, Maxim V. Rakhuba, Stamatios Georgoulis, Menelaos Kanakis, Dengxin Dai, Luc Van Gool:
T-Basis: a Compact Representation for Neural Networks. CoRR abs/2007.06631 (2020) - [i181]Xiankai Lu, Wenguan Wang, Martin Danelljan, Tianfei Zhou, Jianbing Shen, Luc Van Gool:
Video Object Segmentation with Episodic Graph Memory Networks. CoRR abs/2007.07020 (2020) - [i180]Simon Hecker, Dengxin Dai, Alexander Liniger, Luc Van Gool:
Learning Accurate and Human-Like Driving using Semantic Maps and Attention. CoRR abs/2007.07218 (2020) - [i179]Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Luc Van Gool, Dengxin Dai:
Weakly Supervised 3D Object Detection from Lidar Point Cloud. CoRR abs/2007.11901 (2020) - [i178]Menelaos Kanakis, David Bruggemann, Suman Saha, Stamatios Georgoulis, Anton Obukhov, Luc Van Gool:
Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference. CoRR abs/2007.12540 (2020) - [i177]Yan Wu, Aoming Liu, Zhiwu Huang, Siwei Zhang, Luc Van Gool:
Neural Architecture Search as Sparse Supernet. CoRR abs/2007.16112 (2020) - [i176]David Bruggemann, Menelaos Kanakis, Stamatios Georgoulis, Luc Van Gool:
Automated Search for Resource-Efficient Branched Multi-Task Networks. CoRR abs/2008.10292 (2020) - [i175]Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Learning Condition Invariant Features for Retrieval-Based Localization from 1M Images. CoRR abs/2008.12165 (2020) - [i174]Kai Zhang, Yawei Li, Wangmeng Zuo, Lei Zhang, Luc Van Gool, Radu Timofte:
Plug-and-Play Image Restoration with Deep Denoiser Prior. CoRR abs/2008.13751 (2020) - [i173]Prune Truong, Martin Danelljan, Luc Van Gool, Radu Timofte:
GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network. CoRR abs/2009.07823 (2020) - [i172]Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Yu Liu, Luc Van Gool, Matthew B. Blaschko, Tinne Tuytelaars, Marie-Francine Moens:
Commands 4 Autonomous Vehicles (C4AV) Workshop Summary. CoRR abs/2009.08792 (2020) - [i171]Ozan Unal, Luc Van Gool, Dengxin Dai:
Improving Point Cloud Semantic Segmentation by Learning 3D Object Proposal Generation. CoRR abs/2009.10569 (2020) - [i170]Juan-Ting Lin, Dengxin Dai, Luc Van Gool:
Depth Estimation from Monocular Images and Sparse Radar Data. CoRR abs/2010.00058 (2020) - [i169]Ardhendu Shekhar Tripathi, Martin Danelljan, Luc Van Gool, Radu Timofte:
Few-Shot Classification By Few-Iteration Meta-Learning. CoRR abs/2010.00511 (2020) - [i168]Andrés Romero, Luc Van Gool, Radu Timofte:
SMILE: Semantically-guided Multi-attribute Image and Layout Editing. CoRR abs/2010.02315 (2020) - [i167]Ali Varamesh, Ali Diba, Tinne Tuytelaars, Luc Van Gool:
Self-Supervised Ranking for Representation Learning. CoRR abs/2010.07258 (2020) - [i166]Siwei Zhang, Zhiwu Huang, Danda Pani Paudel, Luc Van Gool:
Facial Emotion Recognition with Noisy Multi-task Annotations. CoRR abs/2010.09849 (2020) - [i165]Florin-Alexandru Vasluianu, Andrés Romero, Luc Van Gool, Radu Timofte:
Self-Supervised Shadow Removal. CoRR abs/2010.11619 (2020) - [i164]Yunchao Wei, Shuai Zheng, Ming-Ming Cheng, Hang Zhao, Liwei Wang, Errui Ding, Yi Yang, Antonio Torralba, Ting Liu, Guolei Sun, Wenguan Wang, Luc Van Gool, Wonho Bae, Junhyug Noh, Jinhwan Seo, Gunhee Kim, Hao Zhao, Ming Lu, Anbang Yao, Yiwen Guo, Yurong Chen, Li Zhang, Chuangchuang Tan, Tao Ruan, Guanghua Gu, Shikui Wei, Yao Zhao, Mariia Dobko, Ostap Viniavskyi, Oles Dobosevych, Zhendong Wang, Zhenyuan Chen, Chen Gong, Huanqing Yan, Jun He:
LID 2020: The Learning from Imperfect Data Challenge Results. CoRR abs/2010.11724 (2020)
2010 – 2019
- 2019
- [j139]Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
Video Object Segmentation without Temporal Information. IEEE Trans. Pattern Anal. Mach. Intell. 41(6): 1515-1530 (2019) - [j138]Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao, Dahua Lin, Xiaoou Tang, Luc Van Gool:
Temporal Segment Networks for Action Recognition in Videos. IEEE Trans. Pattern Anal. Mach. Intell. 41(11): 2740-2755 (2019) - [c603]Zhiwu Huang, Jiqing Wu, Luc Van Gool:
Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets. AAAI 2019: 3886-3893 - [c602]Ardhendu Shekhar Tripathi, Martin Danelljan, Luc Van Gool, Radu Timofte:
Tracking the Known and the Unknown by Leveraging Semantic Information. BMVC 2019: 292 - [c601]Ayca Takmaz, Thomas Probst, Danda Pani Paudel, Luc Van Gool:
Learning Feature Representations for Look-Alike Images. CVPR Workshops 2019: 21-24 - [c600]Ali Diba, Vivek Sharma, Rainer Stiefelhagen, Luc Van Gool:
Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks. CVPR Workshops 2019: 601-610 - [c599]Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Unsupervised Learning of Consensus Maximization for 3D Vision Problems. CVPR 2019: 929-938 - [c598]Yuhua Chen, Wen Li, Xiaoran Chen, Luc Van Gool:
Learning Semantic Segmentation From Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach. CVPR 2019: 1841-1850 - [c597]Codruta O. Ancuti, Cosmin Ancuti, Radu Timofte, Luc Van Gool, Lei Zhang, Ming-Hsuan Yang, Tiantong Guo, Xuelu Li, Venkateswararao Cherukuri, Vishal Monga, Hao Jiang, Siyuan Yang, Yan Liu, Xiaochao Qu, Pengfei Wan, Dongwon Park, Se Young Chun, Ming Hong, Jinying Huang, Yizi Chen, Shuxin Chen, Bomin Wang, Pablo Navarrete Michelini, Hanwen Liu, Dan Zhu, Jing Liu, Sanchayan Santra, Ranjan Mondal, Bhabatosh Chanda, Peter Morales, Tzofi Klinghoffer, Le Manh Quan, Yong-Guk Kim, Xiao Liang, Runde Li, Jinshan Pan, Jinhui Tang, Kuldeep Purohit, Maitreya Suin, A. N. Rajagopalan, Raimondo Schettini, Simone Bianco, Flavio Piccoli, Claudio Cusano, Luigi Celona, Sunhee Hwang, Yu Seung Ma, Hyeran Byun, Subrahmanyam Murala, Akshay Dudhane, Harshjeet Singh Aulakh, Tianxiang Zheng, Tao Zhang, Weining Qin, Runnan Zhou, Shanhu Wang, Jean-Philippe Tarel, Chuansheng Wang, Jiawei Wu:
NTIRE 2019 Image Dehazing Challenge Report. CVPR Workshops 2019: 2241-2253 - [c596]Rui Gong, Wen Li, Yuhua Chen, Luc Van Gool:
DLOW: Domain Flow for Adaptation and Generalization. CVPR 2019: 2477-2486 - [c595]Jiqing Wu, Zhiwu Huang, Dinesh Acharya, Wen Li, Janine Thoma, Danda Pani Paudel, Luc Van Gool:
Sliced Wasserstein Generative Models. CVPR 2019: 3713-3722 - [c594]Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Thomas Probst, Luc Van Gool:
Mapping, Localization and Path Planning for Image-Based Navigation Using Visual Features and Map. CVPR 2019: 7383-7391 - [c593]Thomas Probst, Ajad Chhatkuli, Danda Pani Paudel, Luc Van Gool:
What Correspondences Reveal About Unknown Camera and Motion Models? CVPR 2019: 8730-8738 - [c592]Davy Neven, Bert De Brabandere, Marc Proesmans, Luc Van Gool:
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth. CVPR 2019: 8837-8845 - [c591]Yawei Li, Vagia Tsiminaki, Radu Timofte, Marc Pollefeys, Luc Van Gool:
3D Appearance Super-Resolution With Deep Learning. CVPR 2019: 9671-9680 - [c590]Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool:
Practical Full Resolution Learned Lossless Image Compression. CVPR 2019: 10629-10638 - [c589]Chengde Wan, Thomas Probst, Luc Van Gool, Angela Yao:
Self-Supervised 3D Hand Pose Estimation Through Training by Fitting. CVPR 2019: 10853-10862 - [c588]Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Luc Van Gool, Marie-Francine Moens:
Talk2Car: Taking Control of Your Self-Driving Car. EMNLP/IJCNLP (1) 2019: 2088-2098 - [c587]Eirikur Agustsson, Michael Tschannen, Fabian Mentzer, Radu Timofte, Luc Van Gool:
Generative Adversarial Networks for Extreme Learned Image Compression. ICCV 2019: 221-231 - [c586]Qin Wang, Wen Li, Luc Van Gool:
Semi-Supervised Learning by Augmented Distribution Alignment. ICCV 2019: 1466-1475 - [c585]Shuhang Gu, Yawei Li, Luc Van Gool, Radu Timofte:
Self-Guided Network for Fast Image Denoising. ICCV 2019: 2511-2520 - [c584]Shuhang Gu, Wen Li, Luc Van Gool, Radu Timofte:
Fast Image Restoration With Multi-Bin Trainable Linear Units. ICCV 2019: 4189-4198 - [c583]Yawei Li, Shuhang Gu, Luc Van Gool, Radu Timofte:
Learning Filter Basis for Convolutional Neural Network Compression. ICCV 2019: 5622-5631 - [c582]Goutam Bhat, Martin Danelljan, Luc Van Gool, Radu Timofte:
Learning Discriminative Model Prediction for Tracking. ICCV 2019: 6181-6190 - [c581]Ali Diba, Vivek Sharma, Luc Van Gool, Rainer Stiefelhagen:
DynamoNet: Dynamic Action and Motion Network. ICCV 2019: 6191-6200 - [c580]Christos Sakaridis, Dengxin Dai, Luc Van Gool:
Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation. ICCV 2019: 7373-7382 - [c579]Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Convex Relaxations for Consensus and Non-Minimal Problems in 3D Vision. ICCV 2019: 10232-10241 - [c578]Wouter Van Gansbeke, Bert De Brabandere, Davy Neven, Marc Proesmans, Luc Van Gool:
End-to-end Lane Detection through Differentiable Least-Squares Fitting. ICCV Workshops 2019: 905-913 - [c577]Matej Kristan, Amanda Berg, Linyu Zheng, Litu Rout, Luc Van Gool, Luca Bertinetto, Martin Danelljan, Matteo Dunnhofer, Meng Ni, Min Young Kim, Ming Tang, Ming-Hsuan Yang, Abdelrahman Eldesokey, Naveen Paluru, Niki Martinel, Pengfei Xu, Pengfei Zhang, Pengkun Zheng, Pengyu Zhang, Philip H. S. Torr, Qi Zhang, Qiang Wang, Qing Guo, Radu Timofte, Jani Käpylä, Rama Krishna Sai Subrahmanyam Gorthi, Richard M. Everson, Ruize Han, Ruohan Zhang, Shan You, Shao-Chuan Zhao, Shengwei Zhao, Shihu Li, Shikun Li, Shiming Ge, Gustavo Fernández, Shuai Bai, Shuosen Guan, Tengfei Xing, Tianyang Xu, Tianyu Yang, Ting Zhang, Tomás Vojír, Wei Feng, Weiming Hu, Weizhao Wang, Abel Gonzalez-Garcia, Wenjie Tang, Wenjun Zeng, Wenyu Liu, Xi Chen, Xi Qiu, Xiang Bai, Xiao-Jun Wu, Xiaoyun Yang, Xier Chen, Xin Li, Alireza Memarmoghadam, Xing Sun, Xingyu Chen, Xinmei Tian, Xu Tang, Xuefeng Zhu, Yan Huang, Yanan Chen, Yanchao Lian, Yang Gu, Yang Liu, Andong Lu, Yanjie Chen, Yi Zhang, Yinda Xu, Yingming Wang, Yingping Li, Yu Zhou, Yuan Dong, Yufei Xu, Yunhua Zhang, Yunkun Li, Anfeng He, Zeyu Wang Zhao Luo, Zhaoliang Zhang, Zhen-Hua Feng, Zhenyu He, Zhichao Song, Zhihao Chen, Zhipeng Zhang, Zhirong Wu, Zhiwei Xiong, Zhongjian Huang, Anton Varfolomieiev, Zhu Teng, Zihan Ni, Antoni B. Chan, Jiri Matas, Ardhendu Shekhar Tripathi, Arnold W. M. Smeulders, Bala Suraj Pedasingu, Bao Xin Chen, Baopeng Zhang, Baoyuan Wu, Bi Li, Bin He, Bin Yan, Bing Bai, Ales Leonardis, Bing Li, Bo Li, Byeong Hak Kim, Chao Ma, Chen Fang, Chen Qian, Cheng Chen, Chenglong Li, Chengquan Zhang, Chi-Yi Tsai, Michael Felsberg, Chong Luo, Christian Micheloni, Chunhui Zhang, Dacheng Tao, Deepak Gupta, Dejia Song, Dong Wang, Efstratios Gavves, Eunu Yi, Fahad Shahbaz Khan, Roman P. Pflugfelder, Fangyi Zhang, Fei Wang, Fei Zhao, George De Ath, Goutam Bhat, Guangqi Chen, Guangting Wang, Guoxuan Li, Hakan Cevikalp, Hao Du, Joni-Kristian Kämäräinen, Haojie Zhao, Hasan Saribas, Ho Min Jung, Hongliang Bai, Hongyuan Yu, Houwen Peng, Huchuan Lu, Hui Li, Jiakun Li, Luka Cehovin Zajc, Jianhua Li, Jianlong Fu, Jie Chen, Jie Gao, Jie Zhao, Jin Tang, Jing Li, Jingjing Wu, Jingtuo Liu, Jinqiao Wang, Ondrej Drbohlav, Jinqing Qi, Jinyue Zhang, John K. Tsotsos, Jong Hyuk Lee, Joost van de Weijer, Josef Kittler, Jun Ha Lee, Junfei Zhuang, Kangkai Zhang, Kangkang Wang, Alan Lukezic, Kenan Dai, Lei Chen, Lei Liu, Leida Guo, Li Zhang, Liang Wang, Liangliang Wang, Lichao Zhang, Lijun Wang, Lijun Zhou:
The Seventh Visual Object Tracking VOT2019 Challenge Results. ICCV Workshops 2019: 2206-2241 - [c576]Andrés Romero, Pablo Arbeláez, Luc Van Gool, Radu Timofte:
SMIT: Stochastic Multi-Label Image-to-Image Translation. ICCV Workshops 2019: 3285-3294 - [c575]Samarth Shukla, Luc Van Gool, Radu Timofte:
Extremely Weak Supervised Image-to-Image Translation for Semantic Segmentation. ICCV Workshops 2019: 3368-3377 - [c574]Andrey Ignatov, Radu Timofte, Andrei Kulik, Seungsoo Yang, Ke Wang, Felix Baum, Max Wu, Lirong Xu, Luc Van Gool:
AI Benchmark: All About Deep Learning on Smartphones in 2019. ICCV Workshops 2019: 3617-3635 - [c573]Eirikur Agustsson, Alexander Sage, Radu Timofte, Luc Van Gool:
Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models. ICLR (Poster) 2019 - [c572]Liqian Ma, Xu Jia, Stamatios Georgoulis, Tinne Tuytelaars, Luc Van Gool:
Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency. ICLR (Poster) 2019 - [c571]Zheng Liu, Jie Qin, Annan Li, Yunhong Wang, Luc Van Gool:
Adversarial Binary Coding for Efficient Person Re-Identification. ICME 2019: 700-705 - [c570]Asha Anoosheh, Torsten Sattler, Radu Timofte, Marc Pollefeys, Luc Van Gool:
Night-to-Day Image Translation for Retrieval-based Localization. ICRA 2019: 5958-5964 - [c569]Jan-Nico Zaech, Dengxin Dai, Martin Hahner, Luc Van Gool:
Texture Underfitting for Domain Adaptation. ITSC 2019: 547-552 - [c568]Simon Hecker, Alexander Liniger, Henrik Maurenbrecher, Dengxin Dai, Luc Van Gool:
Learning a Curve Guardian for Motorcycles. ITSC 2019: 2984-2991 - [c567]Martin Hahner, Dengxin Dai, Christos Sakaridis, Jan-Nico Zaech, Luc Van Gool:
Semantic Understanding of Foggy Scenes with Purely Synthetic Data. ITSC 2019: 3675-3681 - [c566]Ankit Dhall, Dengxin Dai, Luc Van Gool:
Real-time 3D Traffic Cone Detection for Autonomous Driving. IV 2019: 494-501 - [c565]Wouter Van Gansbeke, Davy Neven, Bert De Brabandere, Luc Van Gool:
Sparse and Noisy LiDAR Completion with RGB Guidance and Uncertainty. MVA 2019: 1-6 - [c564]Yu-Hui Huang, Marc Proesmans, Stamatios Georgoulis, Luc Van Gool:
Uncertainty based model selection for fast semantic segmentation. MVA 2019: 1-6 - [c563]Simon Vandenhende, Bert De Brabandere, Davy Neven, Luc Van Gool:
A Three-Player GAN: Generating Hard Samples to Improve Classification Networks. MVA 2019: 1-6 - [i163]Dengxin Dai, Christos Sakaridis, Simon Hecker, Luc Van Gool:
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding. CoRR abs/1901.01415 (2019) - [i162]Despoina Paschalidou, Ali Osman Ulusoy, Carolin Schmitt, Luc Van Gool, Andreas Geiger:
RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials. CoRR abs/1901.01535 (2019) - [i161]Christos Sakaridis, Dengxin Dai, Luc Van Gool:
Semantic Nighttime Image Segmentation with Synthetic Stylized Data, Gradual Adaptation and Uncertainty-Aware Evaluation. CoRR abs/1901.05946 (2019) - [i160]Bert De Brabandere, Wouter Van Gansbeke, Davy Neven, Marc Proesmans, Luc Van Gool:
End-to-end Lane Detection through Differentiable Least-Squares Fitting. CoRR abs/1902.00293 (2019) - [i159]Ankit Dhall, Dengxin Dai, Luc Van Gool:
Real-time 3D Traffic Cone Detection for Autonomous Driving. CoRR abs/1902.02394 (2019) - [i158]Wouter Van Gansbeke, Davy Neven, Bert De Brabandere, Luc Van Gool:
Sparse and noisy LiDAR completion with RGB guidance and uncertainty. CoRR abs/1902.05356 (2019) - [i157]