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ORCIDVladlen Koltun
Person information
- affiliation: Intel Labs, Santa Clara, CA, USA.
- affiliation: Adobe Research, San Francisco, CA, USA
- affiliation: Stanford University, Computer Science Department, CA, USA
- affiliation: University of California, Berkeley, CA, USA
- affiliation (PhD 2002): Tel Aviv University, Israel
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2020 – today
- 2020
[j48]Antonio Loquercio
, Elia Kaufmann, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Racing: From Simulation to Reality With Domain Randomization. IEEE Trans. Robotics 36(1): 1-14 (2020)- [c107]Christopher Choy, Wei Dong, Vladlen Koltun:
Deep Global Registration. CVPR 2020: 2511-2520 - [c106]John Lambert, Zhuang Liu, Ozan Sener, James Hays, Vladlen Koltun:
MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation. CVPR 2020: 2876-2885 - [c105]Carolin Schmitt, Simon Donné, Gernot Riegler, Vladlen Koltun, Andreas Geiger:
On Joint Estimation of Pose, Geometry and svBRDF From a Handheld Scanner. CVPR 2020: 3490-3500 - [c104]Hengshuang Zhao, Jiaya Jia, Vladlen Koltun:
Exploring Self-Attention for Image Recognition. CVPR 2020: 10073-10082 - [c103]Christopher Choy, Junha Lee, René Ranftl, Jaesik Park, Vladlen Koltun:
High-Dimensional Convolutional Networks for Geometric Pattern Recognition. CVPR 2020: 11224-11233 - [c102]Yiheng Chi, Abhiram Gnanasambandam, Vladlen Koltun, Stanley H. Chan:
Dynamic Low-Light Imaging with Quanta Image Sensors. ECCV (21) 2020: 122-138 - [c101]Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl:
Tracking Objects as Points. ECCV (4) 2020: 474-490 - [c100]Gernot Riegler, Vladlen Koltun:
Free View Synthesis. ECCV (19) 2020: 623-640 - [c99]Philipp Holl, Nils Thuerey, Vladlen Koltun:
Learning to Control PDEs with Differentiable Physics. ICLR 2020 - [c98]Ozan Sener, Vladlen Koltun:
Learning to Guide Random Search. ICLR 2020 - [c97]Benjamin Ummenhofer, Lukas Prantl, Nils Thuerey, Vladlen Koltun:
Lagrangian Fluid Simulation with Continuous Convolutions. ICLR 2020 - [c96]Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav Sukhatme, Vladlen Koltun:
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning. ICML 2020: 7652-7662 - [c95]Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin:
Scalable Differentiable Physics for Learning and Control. ICML 2020: 7847-7856 - [c94]Shaojie Bai, Vladlen Koltun, J. Zico Kolter:
Multiscale Deep Equilibrium Models. NeurIPS 2020 - [i72]Philipp Holl, Vladlen Koltun, Nils Thuerey:
Learning to Control PDEs with Differentiable Physics. CoRR abs/2001.07457 (2020) - [i71]Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl:
Tracking Objects as Points. CoRR abs/2004.01177 (2020) - [i70]Christopher Choy, Wei Dong, Vladlen Koltun:
Deep Global Registration. CoRR abs/2004.11540 (2020) - [i69]Ozan Sener, Vladlen Koltun:
Learning to Guide Random Search. CoRR abs/2004.12214 (2020) - [i68]Hengshuang Zhao, Jiaya Jia, Vladlen Koltun:
Exploring Self-attention for Image Recognition. CoRR abs/2004.13621 (2020) - [i67]Christopher Choy, Junha Lee, René Ranftl, Jaesik Park, Vladlen Koltun:
High-dimensional Convolutional Networks for Geometric Pattern Recognition. CoRR abs/2005.08144 (2020) - [i66]Sohil Atul Shah, Vladlen Koltun:
Auto-decoding Graphs. CoRR abs/2006.02879 (2020) - [i65]Elia Kaufmann, Antonio Loquercio, René Ranftl, Matthias Müller, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Acrobatics. CoRR abs/2006.05768 (2020) - [i64]Shaojie Bai, Vladlen Koltun, J. Zico Kolter:
Multiscale Deep Equilibrium Models. CoRR abs/2006.08656 (2020) - [i63]Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav Sukhatme, Vladlen Koltun:
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning. CoRR abs/2006.11751 (2020) - [i62]Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin:
Scalable Differentiable Physics for Learning and Control. CoRR abs/2007.02168 (2020) - [i61]Artemij Amiranashvili, Nicolai Dorka, Wolfram Burgard, Vladlen Koltun, Thomas Brox:
Scaling Imitation Learning in Minecraft. CoRR abs/2007.02701 (2020) - [i60]Yiheng Chi, Abhiram Gnanasambandam, Vladlen Koltun, Stanley H. Chan:
Dynamic Low-light Imaging with Quanta Image Sensors. CoRR abs/2007.08614 (2020) - [i59]Hexiang Hu, Ozan Sener, Fei Sha, Vladlen Koltun:
Drinking from a Firehose: Continual Learning with Web-scale Natural Language. CoRR abs/2007.09335 (2020) - [i58]Gernot Riegler, Vladlen Koltun:
Free View Synthesis. CoRR abs/2008.05511 (2020) - [i57]Matthias Müller, Vladlen Koltun:
OpenBot: Turning Smartphones into Robots. CoRR abs/2008.10631 (2020) - [i56]Kai Zhang, Gernot Riegler, Noah Snavely, Vladlen Koltun:
NeRF++: Analyzing and Improving Neural Radiance Fields. CoRR abs/2010.07492 (2020) - [i55]Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen, Vladlen Koltun, Marco Hutter:
Learning Quadrupedal Locomotion over Challenging Terrain. CoRR abs/2010.11251 (2020) - [i54]Dhruv Batra, Angel X. Chang, Sonia Chernova, Andrew J. Davison, Jia Deng, Vladlen Koltun, Sergey Levine, Jitendra Malik, Igor Mordatch, Roozbeh Mottaghi, Manolis Savva, Hao Su:
Rearrangement: A Challenge for Embodied AI. CoRR abs/2011.01975 (2020) - [i53]Gernot Riegler, Vladlen Koltun:
Stable View Synthesis. CoRR abs/2011.07233 (2020) - [i52]Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip H. S. Torr, Vladlen Koltun:
Point Transformer. CoRR abs/2012.09164 (2020)
2010 – 2019
- 2019
- [j47]Jan Carius, René Ranftl, Vladlen Koltun, Marco Hutter:
Trajectory Optimization for Legged Robots With Slipping Motions. IEEE Robotics Autom. Lett. 4(3): 3013-3020 (2019) - [j46]Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, Marco Hutter:
Learning agile and dynamic motor skills for legged robots. Sci. Robotics 4(26) (2019) - [j45]Brady Zhou, Philipp Krähenbühl, Vladlen Koltun:
Does computer vision matter for action? Sci. Robotics 4(30) (2019) - [j44]Delio Vicini, Vladlen Koltun, Wenzel Jakob:
A learned shape-adaptive subsurface scattering model. ACM Trans. Graph. 38(4): 127:1-127:15 (2019) - [c93]Dian Chen, Brady Zhou, Vladlen Koltun, Philipp Krähenbühl:
Learning by Cheating. CoRL 2019: 66-75 - [c92]Maxim Tatarchenko, Stephan R. Richter, René Ranftl, Zhuwen Li, Vladlen Koltun, Thomas Brox:
What Do Single-View 3D Reconstruction Networks Learn? CVPR 2019: 3405-3414 - [c91]Xuaner Zhang, Qifeng Chen, Ren Ng, Vladlen Koltun:
Zoom to Learn, Learn to Zoom. CVPR 2019: 3762-3770 - [c90]Henri Rebecq, René Ranftl, Vladlen Koltun, Davide Scaramuzza:
Events-To-Video: Bringing Modern Computer Vision to Event Cameras. CVPR 2019: 3857-3866 - [c89]David B. Lindell, Gordon Wetzstein, Vladlen Koltun:
Acoustic Non-Line-Of-Sight Imaging. CVPR 2019: 6780-6789 - [c88]Gernot Riegler, Yiyi Liao, Simon Donné, Vladlen Koltun, Andreas Geiger:
Connecting the Dots: Learning Representations for Active Monocular Depth Estimation. CVPR 2019: 7624-7633 - [c87]Hyukryul Yang, Hao Ouyang, Vladlen Koltun, Qifeng Chen:
Hiding Video in Audio via Reversible Generative Models. ICCV 2019: 1100-1109 - [c86]Zhipeng Cai, Tat-Jun Chin, Vladlen Koltun:
Consensus Maximization Tree Search Revisited. ICCV 2019: 1637-1645 - [c85]Chen Chen, Qifeng Chen, Minh N. Do, Vladlen Koltun:
Seeing Motion in the Dark. ICCV 2019: 3184-3193 - [c84]Christopher Choy, Jaesik Park, Vladlen Koltun:
Fully Convolutional Geometric Features. ICCV 2019: 8957-8965 - [c83]Manolis Savva, Jitendra Malik, Devi Parikh, Dhruv Batra, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun:
Habitat: A Platform for Embodied AI Research. ICCV 2019: 9338-9346 - [c82]Shaojie Bai, J. Zico Kolter, Vladlen Koltun:
Trellis Networks for Sequence Modeling. ICLR (Poster) 2019 - [c81]Adel Bibi, Bernard Ghanem, Vladlen Koltun, René Ranftl:
Deep Layers as Stochastic Solvers. ICLR (Poster) 2019 - [c80]Elia Kaufmann, Mathias Gehrig, Philipp Foehn, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing. ICRA 2019: 690-696 - [c79]François G. Germain, Qifeng Chen, Vladlen Koltun:
Speech Denoising with Deep Feature Losses. INTERSPEECH 2019: 2723-2727 - [c78]Shaojie Bai, J. Zico Kolter, Vladlen Koltun:
Deep Equilibrium Models. NeurIPS 2019: 688-699 - [c77]Junbang Liang, Ming C. Lin, Vladlen Koltun:
Differentiable Cloth Simulation for Inverse Problems. NeurIPS 2019: 771-780 - [i51]Artemij Amiranashvili, Alexey Dosovitskiy, Vladlen Koltun, Thomas Brox:
Motion Perception in Reinforcement Learning with Dynamic Objects. CoRR abs/1901.03162 (2019) - [i50]Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, Marco Hutter:
Learning agile and dynamic motor skills for legged robots. CoRR abs/1901.08652 (2019) - [i49]Dmytro Mishkin, Alexey Dosovitskiy, Vladlen Koltun:
Benchmarking Classic and Learned Navigation in Complex 3D Environments. CoRR abs/1901.10915 (2019) - [i48]Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun, Jitendra Malik, Devi Parikh, Dhruv Batra:
Habitat: A Platform for Embodied AI Research. CoRR abs/1904.01201 (2019) - [i47]Henri Rebecq, René Ranftl, Vladlen Koltun, Davide Scaramuzza:
Events-to-Video: Bringing Modern Computer Vision to Event Cameras. CoRR abs/1904.08298 (2019) - [i46]Maxim Tatarchenko, Stephan R. Richter, René Ranftl, Zhuwen Li, Vladlen Koltun, Thomas Brox:
What Do Single-view 3D Reconstruction Networks Learn? CoRR abs/1905.03678 (2019) - [i45]Xuaner Cecilia Zhang, Qifeng Chen, Ren Ng, Vladlen Koltun:
Zoom To Learn, Learn To Zoom. CoRR abs/1905.05169 (2019) - [i44]Antonio Loquercio, Elia Kaufmann, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Racing: From Simulation to Reality with Domain Randomization. CoRR abs/1905.09727 (2019) - [i43]Brady Zhou, Philipp Krähenbühl, Vladlen Koltun:
Does computer vision matter for action? CoRR abs/1905.12887 (2019) - [i42]Henri Rebecq, René Ranftl, Vladlen Koltun, Davide Scaramuzza:
High Speed and High Dynamic Range Video with an Event Camera. CoRR abs/1906.07165 (2019) - [i41]Brandon Amos, Vladlen Koltun, J. Zico Kolter:
The Limited Multi-Label Projection Layer. CoRR abs/1906.08707 (2019) - [i40]Katrin Lasinger, René Ranftl, Konrad Schindler, Vladlen Koltun:
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer. CoRR abs/1907.01341 (2019) - [i39]Zhipeng Cai, Tat-Jun Chin, Vladlen Koltun:
Consensus Maximization Tree Search Revisited. CoRR abs/1908.02021 (2019) - [i38]Shaojie Bai, J. Zico Kolter, Vladlen Koltun:
Deep Equilibrium Models. CoRR abs/1909.01377 (2019) - [i37]Dian Chen, Brady Zhou, Vladlen Koltun, Philipp Krähenbühl:
Learning by Cheating. CoRR abs/1912.12294 (2019) - 2018
- [j43]Jakob Engel, Vladlen Koltun, Daniel Cremers:
Direct Sparse Odometry. IEEE Trans. Pattern Anal. Mach. Intell. 40(3): 611-625 (2018) - [j42]Jan Carius, René Ranftl, Vladlen Koltun, Marco Hutter:
Trajectory Optimization With Implicit Hard Contacts. IEEE Robotics Autom. Lett. 3(4): 3316-3323 (2018) - [c76]Matthias Müller, Alexey Dosovitskiy, Bernard Ghanem, Vladlen Koltun:
Driving Policy Transfer via Modularity and Abstraction. CoRL 2018: 1-15 - [c75]Elia Kaufmann, Antonio Loquercio, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Racing: Learning Agile Flight in Dynamic Environments. CoRL 2018: 133-145 - [c74]Artemij Amiranashvili, Alexey Dosovitskiy, Vladlen Koltun, Thomas Brox:
Motion Perception in Reinforcement Learning with Dynamic Objects. CoRL 2018: 156-168 - [c73]Zhuwen Li, Qifeng Chen, Vladlen Koltun:
Interactive Image Segmentation With Latent Diversity. CVPR 2018: 577-585 - [c72]Chen Chen, Qifeng Chen, Jia Xu, Vladlen Koltun:
Learning to See in the Dark. CVPR 2018: 3291-3300 - [c71]Maxim Tatarchenko, Jaesik Park, Vladlen Koltun, Qian-Yi Zhou:
Tangent Convolutions for Dense Prediction in 3D. CVPR 2018: 3887-3896 - [c70]Xiaojuan Qi, Qifeng Chen, Jiaya Jia, Vladlen Koltun:
Semi-Parametric Image Synthesis. CVPR 2018: 8808-8816 - [c69]Felipe Codevilla, Antonio M. López, Vladlen Koltun, Alexey Dosovitskiy:
On Offline Evaluation of Vision-Based Driving Models. ECCV (15) 2018: 246-262 - [c68]René Ranftl, Vladlen Koltun:
Deep Fundamental Matrix Estimation. ECCV (1) 2018: 292-309 - [c67]Artemij Amiranashvili, Alexey Dosovitskiy, Vladlen Koltun, Thomas Brox:
TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning. ICLR (Poster) 2018 - [c66]Shaojie Bai, J. Zico Kolter, Vladlen Koltun:
Convolutional Sequence Modeling Revisited. ICLR (Workshop) 2018 - [c65]Nikolay Savinov, Alexey Dosovitskiy, Vladlen Koltun:
Semi-parametric topological memory for navigation. ICLR (Poster) 2018 - [c64]Felipe Codevilla, Matthias Müller, Antonio M. López, Vladlen Koltun, Alexey Dosovitskiy:
End-to-End Driving Via Conditional Imitation Learning. ICRA 2018: 1-9 - [c63]Ozan Sener, Vladlen Koltun:
Multi-Task Learning as Multi-Objective Optimization. NeurIPS 2018: 525-536 - [c62]Zhuwen Li, Qifeng Chen, Vladlen Koltun:
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search. NeurIPS 2018: 537-546 - [i36]Qian-Yi Zhou, Jaesik Park, Vladlen Koltun:
Open3D: A Modern Library for 3D Data Processing. CoRR abs/1801.09847 (2018) - [i35]Nikolay Savinov, Alexey Dosovitskiy, Vladlen Koltun:
Semi-parametric Topological Memory for Navigation. CoRR abs/1803.00653 (2018) - [i34]Shaojie Bai, J. Zico Kolter, Vladlen Koltun:
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. CoRR abs/1803.01271 (2018) - [i33]Sohil Atul Shah, Vladlen Koltun:
Deep Continuous Clustering. CoRR abs/1803.01449 (2018) - [i32]Matthias Müller, Alexey Dosovitskiy, Bernard Ghanem, Vladlen Koltun:
Driving Policy Transfer via Modularity and Abstraction. CoRR abs/1804.09364 (2018) - [i31]Xiaojuan Qi, Qifeng Chen, Jiaya Jia, Vladlen Koltun:
Semi-parametric Image Synthesis. CoRR abs/1804.10992 (2018) - [i30]Chen Chen, Qifeng Chen, Jia Xu, Vladlen Koltun:
Learning to See in the Dark. CoRR abs/1805.01934 (2018) - [i29]Artemij Amiranashvili, Alexey Dosovitskiy, Vladlen Koltun, Thomas Brox:
TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning. CoRR abs/1806.01175 (2018) - [i28]Elia Kaufmann, Antonio Loquercio, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Deep Drone Racing: Learning Agile Flight in Dynamic Environments. CoRR abs/1806.08548 (2018) - [i27]François G. Germain, Qifeng Chen, Vladlen Koltun:
Speech Denoising with Deep Feature Losses. CoRR abs/1806.10522 (2018) - [i26]Maxim Tatarchenko, Jaesik Park, Vladlen Koltun, Qian-Yi Zhou:
Tangent Convolutions for Dense Prediction in 3D. CoRR abs/1807.02443 (2018) - [i25]Peter Anderson, Angel X. Chang, Devendra Singh Chaplot, Alexey Dosovitskiy, Saurabh Gupta, Vladlen Koltun, Jana Kosecka, Jitendra Malik, Roozbeh Mottaghi, Manolis Savva, Amir Roshan Zamir:
On Evaluation of Embodied Navigation Agents. CoRR abs/1807.06757 (2018) - [i24]Felipe Codevilla, Antonio M. López, Vladlen Koltun, Alexey Dosovitskiy:
On Offline Evaluation of Vision-based Driving Models. CoRR abs/1809.04843 (2018) - [i23]Ozan Sener, Vladlen Koltun:
Multi-Task Learning as Multi-Objective Optimization. CoRR abs/1810.04650 (2018) - [i22]Elia Kaufmann, Mathias Gehrig, Philipp Foehn, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing. CoRR abs/1810.06224 (2018) - [i21]Shaojie Bai, J. Zico Kolter, Vladlen Koltun:
Trellis Networks for Sequence Modeling. CoRR abs/1810.06682 (2018) - [i20]Zhuwen Li, Qifeng Chen, Vladlen Koltun:
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search. CoRR abs/1810.10659 (2018) - [i19]Charles Packer, Katelyn Gao, Jernej Kos, Philipp Krähenbühl, Vladlen Koltun, Dawn Song:
Assessing Generalization in Deep Reinforcement Learning. CoRR abs/1810.12282 (2018) - 2017
- [j41]Sohil Atul Shah, Vladlen Koltun:
Robust continuous clustering. Proc. Natl. Acad. Sci. USA 114(37): 9814-9819 (2017) - [j40]Arno Knapitsch, Jaesik Park, Qian-Yi Zhou, Vladlen Koltun:
Tanks and temples: benchmarking large-scale scene reconstruction. ACM Trans. Graph. 36(4): 78:1-78:13 (2017) - [c61]Alexey Dosovitskiy, Germán Ros, Felipe Codevilla, Antonio M. López, Vladlen Koltun:
CARLA: An Open Urban Driving Simulator. CoRL 2017: 1-16 - [c60]Fisher Yu, Vladlen Koltun, Thomas A. Funkhouser:
Dilated Residual Networks. CVPR 2017: 636-644 - [c59]Jia Xu, René Ranftl, Vladlen Koltun:
Accurate Optical Flow via Direct Cost Volume Processing. CVPR 2017: 5807-5815 - [c58]Jaesik Park, Qian-Yi Zhou, Vladlen Koltun:
Colored Point Cloud Registration Revisited. ICCV 2017: 143-152 - [c57]Marc Khoury, Qian-Yi Zhou, Vladlen Koltun:
Learning Compact Geometric Features. ICCV 2017: 153-161 - [c56]Qifeng Chen, Vladlen Koltun:
Photographic Image Synthesis with Cascaded Refinement Networks. ICCV 2017: 1520-1529 - [c55]Stephan R. Richter, Zeeshan Hayder, Vladlen Koltun:
Playing for Benchmarks. ICCV 2017: 2232-2241 - [c54]Qifeng Chen, Jia Xu, Vladlen Koltun:
Fast Image Processing with Fully-Convolutional Networks. ICCV 2017: 2516-2525 - [c53]Alexey Dosovitskiy, Vladlen Koltun:
Learning to Act by Predicting the Future. ICLR 2017 - [c52]Mohammad Haris Baig, Vladlen Koltun, Lorenzo Torresani:
Learning to Inpaint for Image Compression. NIPS 2017: 1246-1255 - [i18]Jia Xu, René Ranftl, Vladlen Koltun:
Accurate Optical Flow via Direct Cost Volume Processing. CoRR abs/1704.07325 (2017) - [i17]Fisher Yu, Vladlen Koltun, Thomas A. Funkhouser:
Dilated Residual Networks. CoRR abs/1705.09914 (2017) - [i16]Qifeng Chen, Vladlen Koltun:
Photographic Image Synthesis with Cascaded Refinement Networks. CoRR abs/1707.09405 (2017) - [i15]Qifeng Chen, Jia Xu, Vladlen Koltun:
Fast Image Processing with Fully-Convolutional Networks. CoRR abs/1709.00643 (2017) - [i14]Marc Khoury, Qian-Yi Zhou, Vladlen Koltun:
Learning Compact Geometric Features. CoRR abs/1709.05056 (2017) - [i13]Stephan R. Richter, Zeeshan Hayder, Vladlen Koltun:
Playing for Benchmarks. CoRR abs/1709.07322 (2017) - [i12]Mohammad Haris Baig, Vladlen Koltun, Lorenzo Torresani:
Learning to Inpaint for Image Compression. CoRR abs/1709.08855 (2017) - [i11]Felipe Codevilla, Matthias Müller, Alexey Dosovitskiy, Antonio M. López, Vladlen Koltun:
End-to-end Driving via Conditional Imitation Learning. CoRR abs/1710.02410 (2017) - [i10]Alexey Dosovitskiy, Germán Ros, Felipe Codevilla, Antonio M. López, Vladlen Koltun:
CARLA: An Open Urban Driving Simulator. CoRR abs/1711.03938 (2017) - [i9]Manolis Savva, Angel X. Chang, Alexey Dosovitskiy, Thomas A. Funkhouser, Vladlen Koltun:
MINOS: Multimodal Indoor Simulator for Navigation in Complex Environments. CoRR abs/1712.03931 (2017) - 2016
- [c51]Abhijit Kundu, Vibhav Vineet, Vladlen Koltun:
Feature Space Optimization for Semantic Video Segmentation. CVPR 2016: 3168-3175 - [c50]René Ranftl, Vibhav Vineet, Qifeng Chen, Vladlen Koltun:
Dense Monocular Depth Estimation in Complex Dynamic Scenes. CVPR 2016: 4058-4066 - [c49]