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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
- 2021
[j149]Arun Balajee Vasudevan
, Dengxin Dai, Luc Van Gool:
Talk2Nav: Long-Range Vision-and-Language Navigation with Dual Attention and Spatial Memory. Int. J. Comput. Vis. 129(1): 246-266 (2021)- [j148]Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte:
Learning for Video Compression With Recurrent Auto-Encoder and Recurrent Probability Model. IEEE J. Sel. Top. Signal Process. 15(2): 388-401 (2021) - [j147]Timothy Callemein, Tom Roussel, Ali Diba, Floris De Feyter, Wim Boes, Luc Van Eycken, Luc Van Gool, Hugo Van hamme, Tinne Tuytelaars, Toon Goedemé:
Show me where the action is! Multim. Tools Appl. 80(1): 383-408 (2021) - [j146]Liqian Ma, Stamatios Georgoulis, Xu Jia, Luc Van Gool:
FoV-Net: Field-of-View Extrapolation Using Self-Attention and Uncertainty. IEEE Robotics Autom. Lett. 6(3): 4321-4328 (2021) - [c650]Anton Obukhov, Maxim V. Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool:
Spectral Tensor Train Parameterization of Deep Learning Layers. AISTATS 2021: 3547-3555 - [i253]Prune Truong, Martin Danelljan, Luc Van Gool, Radu Timofte:
Learning Accurate Dense Correspondences and When to Trust Them. CoRR abs/2101.01710 (2021) - [i252]Matthieu Paul, Martin Danelljan, Luc Van Gool, Radu Timofte:
Local Memory Attention for Fast Video Semantic Segmentation. CoRR abs/2101.01715 (2021) - [i251]Bin Zhao, Goutam Bhat, Martin Danelljan, Luc Van Gool, Radu Timofte:
Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videos. CoRR abs/2101.02196 (2021) - [i250]Valentin Wolf, Andreas Lugmayr, Martin Danelljan, Luc Van Gool, Radu Timofte:
DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows. CoRR abs/2101.05796 (2021) - [i249]Yan Wu, Zhiwu Huang, Suryansh Kumar, Rhea Sanjay Sukthanker, Radu Timofte, Luc Van Gool:
Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution. CoRR abs/2101.06658 (2021) - [i248]Ke Li, Dengxin Dai, Ender Konukoglu, Luc Van Gool:
Hyperspectral Image Super-Resolution with Spectral Mixup and Heterogeneous Datasets. CoRR abs/2101.07589 (2021) - [i247]Goutam Bhat, Martin Danelljan, Luc Van Gool, Radu Timofte:
Deep Burst Super-Resolution. CoRR abs/2101.10997 (2021) - [i246]Wenguan Wang, Tianfei Zhou, Fisher Yu, Jifeng Dai, Ender Konukoglu, Luc Van Gool:
Exploring Cross-Image Pixel Contrast for Semantic Segmentation. CoRR abs/2101.11939 (2021) - [i245]Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool:
Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. CoRR abs/2102.06191 (2021) - [i244]Mohamad Shahbazi, Zhiwu Huang, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Efficient Conditional GAN Transfer with Knowledge Propagation across Classes. CoRR abs/2102.06696 (2021) - [i243]Anton Obukhov, Maxim V. Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool:
Spectral Tensor Train Parameterization of Deep Learning Layers. CoRR abs/2103.04217 (2021) - [i242]Tianfei Zhou, Wenguan Wang, Si Liu, Yi Yang, Luc Van Gool:
Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing. CoRR abs/2103.04570 (2021) - [i241]M. Saquib Sarfraz, Naila Murray, Vivek Sharma, Ali Diba, Luc Van Gool, Rainer Stiefelhagen:
Temporally-Weighted Hierarchical Clustering for Unsupervised Action Segmentation. CoRR abs/2103.11264 (2021) - [i240]Kai Zhang, Jingyun Liang, Luc Van Gool, Radu Timofte:
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution. CoRR abs/2103.14006 (2021) - [i239]Peshal Agarwal, Danda Pani Paudel, Jan-Nico Zaech, Luc Van Gool:
Unsupervised Robust Domain Adaptation without Source Data. CoRR abs/2103.14577 (2021) - [i238]Jingyun Liang, Kai Zhang, Shuhang Gu, Luc Van Gool, Radu Timofte:
Flow-based Kernel Prior with Application to Blind Super-Resolution. CoRR abs/2103.15977 (2021) - [i237]Christoph Mayer, Martin Danelljan, Danda Pani Paudel, Luc Van Gool:
Learning Target Candidate Association to Keep Track of What Not to Track. CoRR abs/2103.16556 (2021) - [i236]Prune Truong, Martin Danelljan, Fisher Yu, Luc Van Gool:
Warp Consistency for Unsupervised Learning of Dense Correspondences. CoRR abs/2104.03308 (2021) - [i235]Yawei Li, He Chen, Zhaopeng Cui, Radu Timofte, Marc Pollefeys, Gregory Chirikjian, Luc Van Gool:
Towards Efficient Graph Convolutional Networks for Point Cloud Handling. CoRR abs/2104.05706 (2021) - [i234]Yawei Li, Kai Zhang, Jiezhang Cao, Radu Timofte, Luc Van Gool:
LocalViT: Bringing Locality to Vision Transformers. CoRR abs/2104.05707 (2021) - [i233]Jan-Nico Zaech, Dengxin Dai, Alexander Liniger, Martin Danelljan, Luc Van Gool:
Learnable Online Graph Representations for 3D Multi-Object Tracking. CoRR abs/2104.11747 (2021) - [i232]Christos Sakaridis, Dengxin Dai, Luc Van Gool:
ACDC: The Adverse Conditions Dataset with Correspondences for Semantic Driving Scene Understanding. CoRR abs/2104.13395 (2021) - [i231]Qin Wang, Dengxin Dai, Lukas Hoyer, Olga Fink, Luc Van Gool:
Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation. CoRR abs/2104.13613 (2021) - [i230]David Bruggemann, Menelaos Kanakis, Anton Obukhov, Stamatios Georgoulis, Luc Van Gool:
Exploring Relational Context for Multi-Task Dense Prediction. CoRR abs/2104.13874 (2021) - 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) - [c649]David Bruggemann, Menelaos Kanakis, Stamatios Georgoulis, Luc Van Gool:
Automated Search for Resource-Efficient Branched Multi-Task Networks. BMVC 2020 - [c648]Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool, Bert De Brabandere:
Branched Multi-Task Networks: Deciding what layers to share. BMVC 2020 - [c647]Marc Yanlong Zhang, Zhiwu Huang, Danda Pani Paudel, Janine Thoma, Luc Van Gool:
Weakly Paired Multi-Domain Image Translation. BMVC 2020 - [c646]Despoina Paschalidou, Luc Van Gool, Andreas Geiger:
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects From a Single RGB Image. CVPR 2020: 1057-1067 - [c645]Anna Volokitin, Ender Konukoglu, Luc Van Gool:
Decomposing Image Generation into Layout Prediction and Conditional Synthesis. CVPR Workshops 2020: 1530-1538 - [c644]Andrey Ignatov, Luc Van Gool, Radu Timofte:
Replacing Mobile Camera ISP with a Single Deep Learning Model. CVPR Workshops 2020: 2275-2285 - [c643]Kai Zhang, Luc Van Gool, Radu Timofte:
Deep Unfolding Network for Image Super-Resolution. CVPR 2020: 3214-3223 - [c642]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 - [c641]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 - [c640]Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte:
Learning for Video Compression With Hierarchical Quality and Recurrent Enhancement. CVPR 2020: 6627-6636 - [c639]Fabian Mentzer, Luc Van Gool, Michael Tschannen:
Learning Better Lossless Compression Using Lossy Compression. CVPR 2020: 6637-6646 - [c638]Martin Danelljan, Luc Van Gool, Radu Timofte:
Probabilistic Regression for Visual Tracking. CVPR 2020: 7181-7190 - [c637]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 - [c636]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. ECCV Workshops (2) 2020: 3-26 - [c635]Yuhua Chen, Luc Van Gool, Cordelia Schmid, Cristian Sminchisescu:
Consistency Guided Scene Flow Estimation. ECCV (7) 2020: 125-141 - [c634]Goutam Bhat, Martin Danelljan, Luc Van Gool, Radu Timofte:
Know Your Surroundings: Exploiting Scene Information for Object Tracking. ECCV (23) 2020: 205-221 - [c633]Anna Volokitin, Igor Susmelj, Eirikur Agustsson, Luc Van Gool, Radu Timofte:
Efficiently Detecting Plausible Locations for Object Placement Using Masked Convolutions. ECCV Workshops (4) 2020: 252-266 - [c632]Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, Luc Van Gool:
SCAN: Learning to Classify Images Without Labels. ECCV (10) 2020: 268-285 - [c631]Guolei Sun, Salman Khan, Wen Li, Hisham Cholakkal, Fahad Shahbaz Khan, Luc Van Gool:
Fixing Localization Errors to Improve Image Classification. ECCV (25) 2020: 271-287 - [c630]Dario Kneubuehler, Shuhang Gu, Luc Van Gool, Radu Timofte:
Flexible Example-Based Image Enhancement with Task Adaptive Global Feature Self-guided Network. ECCV Workshops (3) 2020: 343-358 - [c629]Guolei Sun, Wenguan Wang, Jifeng Dai, Luc Van Gool:
Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation. ECCV (2) 2020: 347-365 - [c628]Evangelos Ntavelis, Andrés Romero, Iason Kastanis, Luc Van Gool, Radu Timofte:
SESAME: Semantic Editing of Scenes by Adding, Manipulating or Erasing Objects. ECCV (22) 2020: 394-411 - [c627]Frank Verbiest, Marc Proesmans, Luc Van Gool:
Modeling the Effects of Windshield Refraction for Camera Calibration. ECCV (6) 2020: 397-412 - [c626]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 - [c625]Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Luc Van Gool, Dengxin Dai:
Weakly Supervised 3D Object Detection from Lidar Point Cloud. ECCV (13) 2020: 515-531 - [c624]Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool:
MTI-Net: Multi-scale Task Interaction Networks for Multi-task Learning. ECCV (4) 2020: 527-543 - [c623]Clara Fernandez-Labrador, Ajad Chhatkuli, Danda Pani Paudel, Josechu J. Guerrero, Cédric Demonceaux, Luc Van Gool:
Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets. ECCV (25) 2020: 546-563 - [c622]Matej Kristan, Ales Leonardis, Jiri Matas, Michael Felsberg, Roman P. Pflugfelder, Joni-Kristian Kämäräinen, Martin Danelljan, Luka Cehovin Zajc, Alan Lukezic, Ondrej Drbohlav, Linbo He, Yushan Zhang, Song Yan, Jinyu Yang, Gustavo Fernández, Alexander Hauptmann, Alireza Memarmoghadam, Álvaro García-Martín, Andreas Robinson, Anton Varfolomieiev, Awet Haileslassie Gebrehiwot, Bedirhan Uzun, Bin Yan, Bing Li, Chen Qian, Chi-Yi Tsai, Christian Micheloni, Dong Wang, Fei Wang, Fei Xie, Felix Järemo Lawin, Fredrik Gustafsson, Gian Luca Foresti, Goutam Bhat, Guangqi Chen, Haibin Ling, Haitao Zhang, Hakan Cevikalp, Haojie Zhao, Haoran Bai, Hari Chandana Kuchibhotla, Hasan Saribas, Heng Fan, Hossein Ghanei-Yakhdan, Houqiang Li, Houwen Peng, Huchuan Lu, Hui Li, Javad Khaghani, Jesús Bescós, Jianhua Li, Jianlong Fu, Jiaqian Yu, Jingtao Xu, Josef Kittler, Jun Yin, Junhyun Lee, Kaicheng Yu, Kaiwen Liu, Kang Yang, Kenan Dai, Li Cheng, Li Zhang, Lijun Wang, Linyuan Wang, Luc Van Gool, Luca Bertinetto, Matteo Dunnhofer, Miao Cheng, Mohana Murali Dasari, Ning Wang, Pengyu Zhang, Philip H. S. Torr, Qiang Wang, Radu Timofte, Rama Krishna Sai Gorthi, Seokeon Choi, Seyed Mojtaba Marvasti-Zadeh, Shao-Chuan Zhao, Shohreh Kasaei, Shoumeng Qiu, Shuhao Chen, Thomas B. Schön, Tianyang Xu, Wei Lu, Weiming Hu, Wengang Zhou, Xi Qiu, Xiao Ke, Xiao-Jun Wu, Xiaolin Zhang, Xiaoyun Yang, Xuefeng Zhu, Yingjie Jiang, Yingming Wang, Yiwei Chen, Yu Ye, Yuezhou Li, Yuncon Yao, Yunsung Lee, Yuzhang Gu, Zezhou Wang, Zhangyong Tang, Zhen-Hua Feng, Zhijun Mai, Zhipeng Zhang, Zhirong Wu, Ziang Ma:
The Eighth Visual Object Tracking VOT2020 Challenge Results. ECCV Workshops (5) 2020: 547-601 - [c621]Ali Diba, Mohsen Fayyaz, Vivek Sharma, Manohar Paluri, Jürgen Gall, Rainer Stiefelhagen, Luc Van Gool:
Large Scale Holistic Video Understanding. ECCV (5) 2020: 593-610 - [c620]Yawei Li, Shuhang Gu, Kai Zhang, Luc Van Gool, Radu Timofte:
DHP: Differentiable Meta Pruning via HyperNetworks. ECCV (8) 2020: 608-624 - [c619]Arun Balajee Vasudevan, Dengxin Dai, Luc Van Gool:
Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds. ECCV (4) 2020: 638-655 - [c618]Xiankai Lu, Wenguan Wang, Martin Danelljan, Tianfei Zhou, Jianbing Shen, Luc Van Gool:
Video Object Segmentation with Episodic Graph Memory Networks. ECCV (3) 2020: 661-679 - [c617]Menelaos Kanakis, David Bruggemann, Suman Saha, Stamatios Georgoulis, Anton Obukhov, Luc Van Gool:
Reparameterizing Convolutions for Incremental Multi-Task Learning Without Task Interference. ECCV (20) 2020: 689-707 - [c616]Andreas Lugmayr, Martin Danelljan, Luc Van Gool, Radu Timofte:
SRFlow: Learning the Super-Resolution Space with Normalizing Flow. ECCV (5) 2020: 715-732 - [c615]Goutam Bhat, Felix Järemo Lawin, Martin Danelljan, Andreas Robinson, Michael Felsberg, Luc Van Gool, Radu Timofte:
Learning What to Learn for Video Object Segmentation. ECCV (2) 2020: 777-794 - [c614]Kaili Wang, Liqian Ma, José Oramas M., Luc Van Gool, Tinne Tuytelaars:
Unpaired Image-To-Image Shape Translation Across Fashion Data. ICIP 2020: 206-210 - [c613]Anton Obukhov, Maxim V. Rakhuba, Stamatios Georgoulis, Menelaos Kanakis, Dengxin Dai, Luc Van Gool:
T-Basis: a Compact Representation for Neural Networks. ICML 2020: 7392-7404 - [c612]Simon Hecker, Dengxin Dai, Alexander Liniger, Martin Hahner, Luc Van Gool:
Learning Accurate and Human-Like Driving using Semantic Maps and Attention. IROS 2020: 2346-2353 - [c611]Jan-Nico Zaech, Dengxin Dai, Alexander Liniger, Luc Van Gool:
Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Context. IROS 2020: 8982-8989 - [c610]Juan-Ting Lin, Dengxin Dai, Luc Van Gool:
Depth Estimation from Monocular Images and Sparse Radar Data. IROS 2020: 10233-10240 - [c609]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 - [c608]Janine Thoma, Danda Pani Paudel, Luc Van Gool:
Soft Contrastive Learning for Visual Localization. NeurIPS 2020 - [c607]Prune Truong, Martin Danelljan, Luc Van Gool, Radu Timofte:
GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network. NeurIPS 2020 - [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 - [i229]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) - [i228]Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool:
MTI-Net: Multi-Scale Task Interaction Networks for Multi-Task Learning. CoRR abs/2001.06902 (2020) - [i227]Andrey Ignatov, Luc Van Gool, Radu Timofte:
Replacing Mobile Camera ISP with a Single Deep Learning Model. CoRR abs/2002.05509 (2020) - [i226]Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte:
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement. CoRR abs/2003.01966 (2020) - [i225]Arun Balajee Vasudevan, Dengxin Dai, Luc Van Gool:
Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds. CoRR abs/2003.04210 (2020) - [i224]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) - [i223]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) - [i222]Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Geometrically Mappable Image Features. CoRR abs/2003.09682 (2020) - [i221]Fabian Mentzer, Luc Van Gool, Michael Tschannen:
Learning Better Lossless Compression Using Lossy Compression. CoRR abs/2003.10184 (2020) - [i220]Kai Zhang, Luc Van Gool, Radu Timofte:
Deep Unfolding Network for Image Super-Resolution. CoRR abs/2003.10428 (2020) - [i219]Goutam Bhat, Martin Danelljan, Luc Van Gool, Radu Timofte:
Know Your Surroundings: Exploiting Scene Information for Object Tracking. CoRR abs/2003.11014 (2020) - [i218]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) - [i217]Martin Danelljan, Luc Van Gool, Radu Timofte:
Probabilistic Regression for Visual Tracking. CoRR abs/2003.12565 (2020) - [i216]Yawei Li, Shuhang Gu, Kai Zhang, Luc Van Gool, Radu Timofte:
DHP: Differentiable Meta Pruning via HyperNetworks. CoRR abs/2003.13683 (2020) - [i215]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) - [i214]Martin Hahner, Dengxin Dai, Alexander Liniger, Luc Van Gool:
Quantifying Data Augmentation for LiDAR based 3D Object Detection. CoRR abs/2004.01643 (2020) - [i213]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) - [i212]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) - [i211]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) - [i210]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) - [i209]Alexander Liniger, Luc Van Gool:
Safe Motion Planning for Autonomous Driving using an Adversarial Road Model. CoRR abs/2005.07691 (2020) - [i208]Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, Luc Van Gool:
Learning To Classify Images Without Labels. CoRR abs/2005.12320 (2020) - [i207]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) - [i206]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) - [i205]Yuhua Chen, Luc Van Gool, Cordelia Schmid, Cristian Sminchisescu:
Consistency Guided Scene Flow Estimation. CoRR abs/2006.11242 (2020) - [i204]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) - [i203]Andreas Lugmayr, Martin Danelljan, Luc Van Gool, Radu Timofte:
SRFlow: Learning the Super-Resolution Space with Normalizing Flow. CoRR abs/2006.14200 (2020) - [i202]Rui Gong, Dengxin Dai, Yuhua Chen, Wen Li, Luc Van Gool:
Analogical Image Translation for Fog Generation. CoRR abs/2006.15618 (2020) - [i201]Ren Yang, Luc Van Gool, Radu Timofte:
OpenDVC: An Open Source Implementation of the DVC Video Compression Method. CoRR abs/2006.15862 (2020) - [i200]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) - [i199]Guolei Sun, Wenguan Wang, Jifeng Dai, Luc Van Gool:
Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation. CoRR abs/2007.01947 (2020) - [i198]Rui Gong, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool:
Self-Calibration Supported Robust Projective Structure-from-Motion. CoRR abs/2007.02045 (2020) - [i197]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) - [i196]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) - [i195]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) - [i194]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) - [i193]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) - [i192]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) - [i191]Yan Wu, Aoming Liu, Zhiwu Huang, Siwei Zhang, Luc Van Gool:
Neural Architecture Search as Sparse Supernet. CoRR abs/2007.16112 (2020) - [i190]David Bruggemann, Menelaos Kanakis, Stamatios Georgoulis, Luc Van Gool:
Automated Search for Resource-Efficient Branched Multi-Task Networks. CoRR abs/2008.10292 (2020) - [i189]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) - [i188]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) - [i187]Prune Truong, Martin Danelljan, Luc Van Gool, Radu Timofte:
GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network. CoRR abs/2009.07823 (2020) - [i186]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) - [i185]Ozan Unal, Luc Van Gool, Dengxin Dai:
Improving Point Cloud Semantic Segmentation by Learning 3D Object Proposal Generation. CoRR abs/2009.10569 (2020) - [i184]Juan-Ting Lin, Dengxin Dai, Luc Van Gool:
Depth Estimation from Monocular Images and Sparse Radar Data. CoRR abs/2010.00058 (2020)