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2020 – today
- 2024
[c80]Matthew Kowal, Achal Dave, Rares Ambrus, Adrien Gaidon, Konstantinos G. Derpanis, Pavel Tokmakov:
Understanding Video Transformers via Universal Concept Discovery. CVPR 2024: 10946-10956- [c79]Shun Iwase, Katherine Liu, Vitor Guizilini, Adrien Gaidon, Kris Kitani, Rares Ambrus, Sergey Zakharov:
Zero-Shot Multi-object Scene Completion. ECCV (3) 2024: 96-113 - [c78]Sergey Zakharov
, Katherine Liu, Adrien Gaidon, Rares Ambrus:
ReFiNe: Recursive Field Networks for Cross-Modal Multi-Scene Representation. SIGGRAPH (Conference Paper Track) 2024: 100 - [i84]Matthew Kowal, Achal Dave, Rares Ambrus, Adrien Gaidon, Konstantinos G. Derpanis, Pavel Tokmakov:
Understanding Video Transformers via Universal Concept Discovery. CoRR abs/2401.10831 (2024) - [i83]Shun Iwase, Katherine Liu, Vitor Guizilini, Adrien Gaidon, Kris Kitani, Rares Ambrus, Sergey Zakharov:
Zero-Shot Multi-Object Shape Completion. CoRR abs/2403.14628 (2024) - [i82]Muhammad Zubair Irshad, Sergey Zakharov, Vitor Guizilini, Adrien Gaidon, Zsolt Kira, Rares Ambrus:
NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields. CoRR abs/2404.01300 (2024) - [i81]Jean Mercat, Igor Vasiljevic, Sedrick Keh, Kushal Arora, Achal Dave, Adrien Gaidon, Thomas Kollar:
Linearizing Large Language Models. CoRR abs/2405.06640 (2024) - [i80]Sergey Zakharov, Katherine Liu, Adrien Gaidon, Rares Ambrus:
ReFiNe: Recursive Field Networks for Cross-modal Multi-scene Representation. CoRR abs/2406.04309 (2024) - 2023
- [c77]Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal:
Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? CLeaR 2023: 386-407 - [c76]Stephen Tian, Yancheng Cai, Hong-Xing Yu, Sergey Zakharov, Katherine Liu, Adrien Gaidon, Yunzhu Li, Jiajun Wu:
Multi-Object Manipulation via Object-Centric Neural Scattering Functions. CVPR 2023: 9021-9031 - [c75]Dian Chen, Jie Li, Vitor Guizilini, Rares Ambrus, Adrien Gaidon:
Viewpoint Equivariance for Multi-View 3D Object Detection. CVPR 2023: 9213-9222 - [c74]Pavel Tokmakov, Jie Li, Adrien Gaidon:
Breaking the "Object" in Video Object Segmentation. CVPR 2023: 22836-22845 - [c73]Zhipeng Bao, Pavel Tokmakov, Yu-Xiong Wang, Adrien Gaidon, Martial Hebert:
Object Discovery from Motion-Guided Tokens. CVPR 2023: 22972-22981 - [c72]Muhammad Zubair Irshad, Sergey Zakharov, Katherine Liu, Vitor Guizilini, Thomas Kollar, Adrien Gaidon, Zsolt Kira, Rares Ambrus:
NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes. ICCV 2023: 9153-9164 - [c71]Vitor Guizilini, Igor Vasiljevic, Dian Chen, Rares Ambrus, Adrien Gaidon:
Towards Zero-Shot Scale-Aware Monocular Depth Estimation. ICCV 2023: 9199-9209 - [c70]Vitor Guizilini, Igor Vasiljevic, Jiading Fang, Rares Ambrus, Sergey Zakharov, Vincent Sitzmann, Adrien Gaidon:
DeLiRa: Self-Supervised Depth, Light, and Radiance Fields. ICCV 2023: 17889-17899 - [c69]Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Andrei Ambrus, Adrien Gaidon, William T. Freeman, Frédo Durand, Joshua B. Tenenbaum, Vincent Sitzmann:
Neural Groundplans: Persistent Neural Scene Representations from a Single Image. ICLR 2023 - [c68]Dennis Park, Jie Li, Dian Chen, Vitor Guizilini, Adrien Gaidon:
Depth Is All You Need for Monocular 3D Detection. ICRA 2023: 7024-7031 - [c67]Takayuki Kanai, Igor Vasiljevic, Vitor Guizilini, Adrien Gaidon, Rares Ambrus:
Robust Self-Supervised Extrinsic Self-Calibration. IROS 2023: 1932-1939 - [c66]Fernando Castañeda, Haruki Nishimura, Rowan Thomas McAllister, Koushil Sreenath, Adrien Gaidon:
In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States. L4DC 2023: 286-299 - [i79]Fernando Castañeda, Haruki Nishimura, Rowan McAllister, Koushil Sreenath, Adrien Gaidon:
In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States. CoRR abs/2301.12012 (2023) - [i78]Dian Chen, Jie Li, Vitor Guizilini, Rares Ambrus, Adrien Gaidon:
Viewpoint Equivariance for Multi-View 3D Object Detection. CoRR abs/2303.14548 (2023) - [i77]Zhipeng Bao, Pavel Tokmakov, Yu-Xiong Wang, Adrien Gaidon, Martial Hebert:
Object Discovery from Motion-Guided Tokens. CoRR abs/2303.15555 (2023) - [i76]Vitor Guizilini, Igor Vasiljevic, Jiading Fang, Rares Ambrus, Sergey Zakharov, Vincent Sitzmann, Adrien Gaidon:
DeLiRa: Self-Supervised Depth, Light, and Radiance Fields. CoRR abs/2304.02797 (2023) - [i75]Jiading Fang, Shengjie Lin, Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Adrien Gaidon, Gregory Shakhnarovich, Matthew R. Walter:
NeRFuser: Large-Scale Scene Representation by NeRF Fusion. CoRR abs/2305.13307 (2023) - [i74]Anirudh Sriram, Adrien Gaidon, Jiajun Wu, Juan Carlos Niebles, Li Fei-Fei, Ehsan Adeli:
HomE: Homography-Equivariant Video Representation Learning. CoRR abs/2306.01623 (2023) - [i73]Stephen Tian, Yancheng Cai, Hong-Xing Yu, Sergey Zakharov, Katherine Liu, Adrien Gaidon, Yunzhu Li, Jiajun Wu:
Multi-Object Manipulation via Object-Centric Neural Scattering Functions. CoRR abs/2306.08748 (2023) - [i72]Vitor Guizilini, Igor Vasiljevic, Dian Chen, Rares Ambrus, Adrien Gaidon:
Towards Zero-Shot Scale-Aware Monocular Depth Estimation. CoRR abs/2306.17253 (2023) - [i71]Takayuki Kanai, Igor Vasiljevic, Vitor Guizilini, Adrien Gaidon, Rares Ambrus:
Robust Self-Supervised Extrinsic Self-Calibration. CoRR abs/2308.02153 (2023) - [i70]Muhammad Zubair Irshad, Sergey Zakharov, Katherine Liu, Vitor Guizilini, Thomas Kollar, Adrien Gaidon, Zsolt Kira, Rares Ambrus:
NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes. CoRR abs/2308.12967 (2023) - [i69]Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal:
Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? CoRR abs/2312.17168 (2023) - 2022
- [j8]Vitor Guizilini, Kuan-Hui Lee, Rares Ambrus, Adrien Gaidon:
Learning Optical Flow, Depth, and Scene Flow Without Real-World Labels. IEEE Robotics Autom. Lett. 7(2): 3491-3498 (2022) - [j7]Vitor Guizilini, Igor Vasiljevic, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon:
Full Surround Monodepth From Multiple Cameras. IEEE Robotics Autom. Lett. 7(2): 5397-5404 (2022) - [c65]Haruki Nishimura, Jean Mercat, Blake Wulfe, Rowan Thomas McAllister, Adrien Gaidon:
RAP: Risk-Aware Prediction for Robust Planning. CoRL 2022: 381-392 - [c64]Xiangru Huang, Yue Wang, Vitor Campanholo Guizilini, Rares Andrei Ambrus, Adrien Gaidon, Justin M. Solomon:
Representation Learning for Object Detection from Unlabeled Point Cloud Sequences. CoRL 2022: 1277-1288 - [c63]Sergey Zakharov, Rares Andrei Ambrus, Katherine Liu, Adrien Gaidon:
ROAD: Learning an Implicit Recursive Octree Auto-Decoder to Efficiently Encode 3D Shapes. CoRL 2022: 2136-2147 - [c62]Vitor Guizilini, Rares Ambrus, Dian Chen, Sergey Zakharov, Adrien Gaidon:
Multi-Frame Self-Supervised Depth with Transformers. CVPR 2022: 160-170 - [c61]Shyamal Buch, Cristóbal Eyzaguirre, Adrien Gaidon, Jiajun Wu, Li Fei-Fei, Juan Carlos Niebles:
Revisiting the "Video" in Video-Language Understanding. CVPR 2022: 2907-2917 - [c60]Zhipeng Bao, Pavel Tokmakov, Allan Jabri, Yu-Xiong Wang, Adrien Gaidon, Martial Hebert:
Discovering Objects that Can Move. CVPR 2022: 11779-11788 - [c59]Vitor Guizilini, Igor Vasiljevic, Jiading Fang, Rare Ambru, Greg Shakhnarovich, Matthew R. Walter, Adrien Gaidon:
Depth Field Networks For Generalizable Multi-view Scene Representation. ECCV (32) 2022: 245-262 - [c58]Muhammad Zubair Irshad, Sergey Zakharov, Rares Ambrus, Thomas Kollar, Zsolt Kira, Adrien Gaidon:
ShAPO: Implicit Representations for Multi-object Shape, Appearance, and Pose Optimization. ECCV (2) 2022: 275-292 - [c57]Sergey Zakharov, Rares Ambrus, Vitor Guizilini, Wadim Kehl, Adrien Gaidon:
Photo-realistic Neural Domain Randomization. ECCV (25) 2022: 310-327 - [c56]Xinshuo Weng, Junyu Nan, Kuan-Hui Lee, Rowan McAllister, Adrien Gaidon, Nicholas Rhinehart, Kris M. Kitani:
S2Net: Stochastic Sequential Pointcloud Forecasting. ECCV (27) 2022: 549-564 - [c55]Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma:
Self-supervised Learning is More Robust to Dataset Imbalance. ICLR 2022 - [c54]Blake Wulfe, Logan Michael Ellis, Jean Mercat, Rowan Thomas McAllister, Adrien Gaidon:
Dynamics-Aware Comparison of Learned Reward Functions. ICLR 2022 - [c53]Pavel Tokmakov, Allan Jabri, Jie Li, Adrien Gaidon:
Object Permanence Emerges in a Random Walk along Memory. ICML 2022: 21506-21519 - [c52]Rowan McAllister, Blake Wulfe, Jean Mercat, Logan Ellis, Sergey Levine, Adrien Gaidon:
Control-Aware Prediction Objectives for Autonomous Driving. ICRA 2022: 1-8 - [c51]Jiading Fang, Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon, Matthew R. Walter:
Self-Supervised Camera Self-Calibration from Video. ICRA 2022: 8468-8475 - [c50]Boris Ivanovic, Kuan-Hui Lee, Pavel Tokmakov, Blake Wulfe, Rowan McAllister, Adrien Gaidon, Marco Pavone:
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty. IROS 2022: 12196-12203 - [i68]Blake Wulfe, Ashwin Balakrishna, Logan Ellis, Jean Mercat, Rowan McAllister, Adrien Gaidon:
Dynamics-Aware Comparison of Learned Reward Functions. CoRR abs/2201.10081 (2022) - [i67]Zhipeng Bao, Pavel Tokmakov, Allan Jabri, Yu-Xiong Wang, Adrien Gaidon, Martial Hebert:
Discovering Objects that Can Move. CoRR abs/2203.10159 (2022) - [i66]Vitor Guizilini, Kuan-Hui Lee, Rares Ambrus, Adrien Gaidon:
Learning Optical Flow, Depth, and Scene Flow without Real-World Labels. CoRR abs/2203.15089 (2022) - [i65]Pavel Tokmakov, Allan Jabri, Jie Li, Adrien Gaidon:
Object Permanence Emerges in a Random Walk along Memory. CoRR abs/2204.01784 (2022) - [i64]Vitor Guizilini, Rares Ambrus, Dian Chen, Sergey Zakharov, Adrien Gaidon:
Multi-Frame Self-Supervised Depth with Transformers. CoRR abs/2204.07616 (2022) - [i63]Rowan McAllister, Blake Wulfe, Jean Mercat, Logan Ellis, Sergey Levine, Adrien Gaidon:
Control-Aware Prediction Objectives for Autonomous Driving. CoRR abs/2204.13319 (2022) - [i62]Shyamal Buch, Cristóbal Eyzaguirre, Adrien Gaidon, Jiajun Wu, Li Fei-Fei, Juan Carlos Niebles:
Revisiting the "Video" in Video-Language Understanding. CoRR abs/2206.01720 (2022) - [i61]Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Ambrus, Adrien Gaidon, William T. Freeman, Frédo Durand, Joshua B. Tenenbaum, Vincent Sitzmann:
Seeing 3D Objects in a Single Image via Self-Supervised Static-Dynamic Disentanglement. CoRR abs/2207.11232 (2022) - [i60]Muhammad Zubair Irshad, Sergey Zakharov, Rares Ambrus, Thomas Kollar, Zsolt Kira, Adrien Gaidon:
ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization. CoRR abs/2207.13691 (2022) - [i59]Vitor Guizilini, Igor Vasiljevic, Jiading Fang, Rares Ambrus, Greg Shakhnarovich, Matthew R. Walter, Adrien Gaidon:
Depth Field Networks for Generalizable Multi-view Scene Representation. CoRR abs/2207.14287 (2022) - [i58]Haruki Nishimura, Jean Mercat, Blake Wulfe, Rowan McAllister, Adrien Gaidon:
RAP: Risk-Aware Prediction for Robust Planning. CoRR abs/2210.01368 (2022) - [i57]Dennis Park, Jie Li, Dian Chen, Vitor Guizilini, Adrien Gaidon:
Depth Is All You Need for Monocular 3D Detection. CoRR abs/2210.02493 (2022) - [i56]Sergey Zakharov, Rares Ambrus, Vitor Guizilini, Wadim Kehl, Adrien Gaidon:
Photo-realistic Neural Domain Randomization. CoRR abs/2210.12682 (2022) - [i55]Sergey Zakharov, Rares Ambrus, Katherine Liu, Adrien Gaidon:
ROAD: Learning an Implicit Recursive Octree Auto-Decoder to Efficiently Encode 3D Shapes. CoRR abs/2212.06193 (2022) - [i54]Pavel Tokmakov, Jie Li, Adrien Gaidon:
Breaking the "Object" in Video Object Segmentation. CoRR abs/2212.06200 (2022) - 2021
- [j6]Haruki Nishimura, Negar Mehr, Adrien Gaidon, Mac Schwager:
RAT iLQR: A Risk Auto-Tuning Controller to Optimally Account for Stochastic Model Mismatch. IEEE Robotics Autom. Lett. 6(2): 763-770 (2021) - [c49]Sergey Zakharov, Rares Andrei Ambrus, Vitor Guizilini, Dennis Park, Wadim Kehl, Frédo Durand, Joshua B. Tenenbaum, Vincent Sitzmann, Jiajun Wu, Adrien Gaidon:
Single-Shot Scene Reconstruction. CoRL 2021: 501-512 - [c48]Nishant Rai, Ehsan Adeli, Kuan-Hui Lee, Adrien Gaidon, Juan Carlos Niebles:
CoCon: Cooperative-Contrastive Learning. CVPR Workshops 2021: 3384-3393 - [c47]Vitor Guizilini, Rares Ambrus, Wolfram Burgard, Adrien Gaidon:
Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion. CVPR 2021: 11078-11088 - [c46]Tommi Kerola, Jie Li, Atsushi Kanehira, Yasunori Kudo, Alexis Vallet, Adrien Gaidon:
Hierarchical Lovasz Embeddings for Proposal-Free Panoptic Segmentation. CVPR 2021: 14413-14423 - [c45]Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, Adrien Gaidon:
Is Pseudo-Lidar needed for Monocular 3D Object detection? ICCV 2021: 3122-3132 - [c44]Vitor Guizilini, Jie Li, Rares Ambrus, Adrien Gaidon:
Geometric Unsupervised Domain Adaptation for Semantic Segmentation. ICCV 2021: 8517-8527 - [c43]Pavel Tokmakov, Jie Li, Wolfram Burgard, Adrien Gaidon:
Learning to Track with Object Permanence. ICCV 2021: 10840-10849 - [c42]Aditya Ganeshan, Alexis Vallet, Yasunori Kudo, Shin-ichi Maeda, Tommi Kerola, Rares Ambrus, Dennis Park, Adrien Gaidon:
Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency. ICCV 2021: 15479-15489 - [c41]Kaidi Cao, Yining Chen, Junwei Lu, Nikos Aréchiga, Adrien Gaidon, Tengyu Ma:
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization. ICLR 2021 - [c40]Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma:
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. NeurIPS 2021: 5000-5011 - [c39]Rares Ambrus, Vitor Guizilini, Naveen Kuppuswamy, Andrew Beaulieu, Adrien Gaidon, Alex Alspach:
Monocular Depth Estimation for Soft Visuotactile Sensors. RoboSoft 2021: 643-649 - [i53]Rares Ambrus, Vitor Guizilini, Naveen Kuppuswamy, Andrew Beaulieu, Adrien Gaidon, Alex Alspach:
Monocular Depth Estimation for Soft Visuotactile Sensors. CoRR abs/2101.01677 (2021) - [i52]Pavel Tokmakov, Jie Li, Wolfram Burgard, Adrien Gaidon:
Learning to Track with Object Permanence. CoRR abs/2103.14258 (2021) - [i51]Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. CoRR abs/2103.15332 (2021) - [i50]Vitor Guizilini, Rares Ambrus, Wolfram Burgard, Adrien Gaidon:
Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion. CoRR abs/2103.16690 (2021) - [i49]Vitor Guizilini, Jie Li, Rares Ambrus, Adrien Gaidon:
Geometric Unsupervised Domain Adaptation for Semantic Segmentation. CoRR abs/2103.16694 (2021) - [i48]Vitor Guizilini, Igor Vasiljevic, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon:
Full Surround Monodepth from Multiple Cameras. CoRR abs/2104.00152 (2021) - [i47]Boris Ivanovic, Kuan-Hui Lee, Pavel Tokmakov, Blake Wulfe, Rowan McAllister, Adrien Gaidon, Marco Pavone:
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty. CoRR abs/2104.12446 (2021) - [i46]Nishant Rai, Ehsan Adeli, Kuan-Hui Lee, Adrien Gaidon, Juan Carlos Niebles:
CoCon: Cooperative-Contrastive Learning. CoRR abs/2104.14764 (2021) - [i45]Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma:
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. CoRR abs/2106.04156 (2021) - [i44]Tommi Kerola, Jie Li, Atsushi Kanehira, Yasunori Kudo, Alexis Vallet, Adrien Gaidon:
Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation. CoRR abs/2106.04555 (2021) - [i43]Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, Adrien Gaidon:
Is Pseudo-Lidar needed for Monocular 3D Object detection? CoRR abs/2108.06417 (2021) - [i42]Aditya Ganeshan, Alexis Vallet, Yasunori Kudo, Shin-ichi Maeda, Tommi Kerola, Rares Ambrus, Dennis Park, Adrien Gaidon:
Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency. CoRR abs/2109.13432 (2021) - [i41]Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma:
Self-supervised Learning is More Robust to Dataset Imbalance. CoRR abs/2110.05025 (2021) - [i40]Jiading Fang, Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon, Matthew R. Walter:
Self-Supervised Camera Self-Calibration from Video. CoRR abs/2112.03325 (2021) - 2020
- [j5]César Roberto de Souza, Adrien Gaidon, Yohann Cabon, Naila Murray, Antonio M. López:
Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models. Int. J. Comput. Vis. 128(5): 1505-1536 (2020) - [j4]Bingbin Liu, Ehsan Adeli, Zhangjie Cao, Kuan-Hui Lee, Abhijeet Shenoi, Adrien Gaidon, Juan Carlos Niebles:
Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction. IEEE Robotics Autom. Lett. 5(2): 3485-3492 (2020) - [c38]Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Wolfram Burgard, Greg Shakhnarovich, Adrien Gaidon:
Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion. 3DV 2020: 1-11 - [c37]Jiexiong Tang, Rares Ambrus, Vitor Guizilini, Sudeep Pillai, Hanme Kim, Patric Jensfelt, Adrien Gaidon:
Self-Supervised 3D Keypoint Learning for Ego-Motion Estimation. CoRL 2020: 2085-2103 - [c36]Boris Ivanovic, Amine Elhafsi, Guy Rosman, Adrien Gaidon, Marco Pavone:
MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control. CoRL 2020: 2243-2256 - [c35]Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Allan Raventos, Adrien Gaidon:
3D Packing for Self-Supervised Monocular Depth Estimation. CVPR 2020: 2482-2491 - [c34]Rui Hou, Jie Li, Arjun Bhargava, Allan Raventos, Vitor Guizilini, Chao Fang, Jerome P. Lynch, Adrien Gaidon:
Real-Time Panoptic Segmentation From Dense Detections. CVPR 2020: 8520-8529 - [c33]Boxiao Pan, Haoye Cai, De-An Huang, Kuan-Hui Lee, Adrien Gaidon, Ehsan Adeli, Juan Carlos Niebles:
Spatio-Temporal Graph for Video Captioning With Knowledge Distillation. CVPR 2020: 10867-10876 - [c32]Sergey Zakharov, Wadim Kehl, Arjun Bhargava, Adrien Gaidon:
Autolabeling 3D Objects With Differentiable Rendering of SDF Shape Priors. CVPR 2020: 12221-12230 - [c31]Deniz Beker, Hiroharu Kato, Mihai Morariu, Takahiro Ando, Toru Matsuoka, Wadim Kehl, Adrien Gaidon:
Monocular Differentiable Rendering for Self-supervised 3D Object Detection. ECCV (21) 2020: 514-529 - [c30]Karttikeya Mangalam, Harshayu Girase, Shreyas Agarwal, Kuan-Hui Lee, Ehsan Adeli, Jitendra Malik, Adrien Gaidon:
It Is Not the Journey But the Destination: Endpoint Conditioned Trajectory Prediction. ECCV (2) 2020: 759-776 - [c29]Vitor Guizilini, Rui Hou, Jie Li, Rares Ambrus, Adrien Gaidon:
Semantically-Guided Representation Learning for Self-Supervised Monocular Depth. ICLR 2020 - [c28]Kuan-Hui Lee, Matthew Kliemann, Adrien Gaidon, Jie Li, Chao Fang, Sudeep Pillai, Wolfram Burgard:
PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving. IROS 2020: 2007-2013 - [c27]Shinya Shiroshita, Shirou Maruyama, Daisuke Nishiyama, Mario Ynocente Castro, Karim Hamzaoui, Guy Rosman, Jonathan A. DeCastro, Kuan-Hui Lee, Adrien Gaidon:
Behaviorally Diverse Traffic Simulation via Reinforcement Learning. IROS 2020: 2103-2110 - [c26]Andreas Bühler, Adrien Gaidon, Andrei Cramariuc, Rares Ambrus, Guy Rosman, Wolfram Burgard:
Driving Through Ghosts: Behavioral Cloning with False Positives. IROS 2020: 5431-5437 - [c25]Mingyu Wang, Negar Mehr, Adrien Gaidon, Mac Schwager:
Game-Theoretic Planning for Risk-Aware Interactive Agents. IROS 2020: 6998-7005 - [c24]Haruki Nishimura, Boris Ivanovic, Adrien Gaidon, Marco Pavone, Mac Schwager:
Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction. IROS 2020: 11205-11212 - [c23]Daisuke Nishiyama, Mario Ynocente Castro, Shirou Maruyama, Shinya Shiroshita, Karim Hamzaoui, Yi Ouyang, Guy Rosman, Jonathan A. DeCastro, Kuan-Hui Lee, Adrien Gaidon:
Discovering Avoidable Planner Failures of Autonomous Vehicles using Counterfactual Analysis in Behaviorally Diverse Simulation. ITSC 2020: 1-8 - [c22]Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. NeurIPS (Competition and Demos) 2020: 361-395 - [c21]Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh:
Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving. Robotics: Science and Systems 2020 - [c20]Karttikeya Mangalam, Ehsan Adeli, Kuan-Hui Lee, Adrien Gaidon, Juan Carlos Niebles:
Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision. WACV 2020: 2773-2782 - [i39]Bingbin Liu, Ehsan Adeli, Zhangjie Cao, Kuan-Hui Lee, Abhijeet Shenoi, Adrien Gaidon, Juan Carlos Niebles:
Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction. CoRR abs/2002.08945 (2020) - [i38]Vitor Guizilini, Rui Hou, Jie Li, Rares Ambrus, Adrien Gaidon:
Semantically-Guided Representation Learning for Self-Supervised Monocular Depth. CoRR abs/2002.12319 (2020) - [i37]Boxiao Pan, Haoye Cai, De-An Huang, Kuan-Hui Lee, Adrien Gaidon, Ehsan Adeli, Juan Carlos Niebles:
Spatio-Temporal Graph for Video Captioning with Knowledge Distillation. CoRR abs/2003.13942 (2020) - [i36]Karttikeya Mangalam, Harshayu Girase, Shreyas Agarwal, Kuan-Hui Lee, Ehsan Adeli, Jitendra Malik, Adrien Gaidon:
It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction. CoRR abs/2004.02025 (2020) - [i35]Hiroharu Kato, Deniz Beker, Mihai Morariu, Takahiro Ando, Toru Matsuoka, Wadim Kehl, Adrien Gaidon:
Differentiable Rendering: A Survey. CoRR abs/2006.12057 (2020) - [i34]Kaidi Cao, Yining Chen, Junwei Lu, Nikos Aréchiga, Adrien Gaidon, Tengyu Ma:
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization. CoRR abs/2006.15766 (2020) - [i33]Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh:
Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving. CoRR abs/2007.00178 (2020) - [i32]Kuan-Hui Lee, Matthew Kliemann, Adrien Gaidon, Jie Li, Chao Fang, Sudeep Pillai, Wolfram Burgard:
PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving. CoRR abs/2008.01179 (2020) - [i31]Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Wolfram Burgard, Greg Shakhnarovich, Adrien Gaidon:
Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion. CoRR abs/2008.06630 (2020) - [i30]Andreas Bühler, Adrien Gaidon, Andrei Cramariuc, Rares Ambrus, Guy Rosman, Wolfram Burgard:
Driving Through Ghosts: Behavioral Cloning with False Positives. CoRR abs/2008.12969 (2020) - [i29]Haruki Nishimura, Boris Ivanovic, Adrien Gaidon, Marco Pavone, Mac Schwager:
Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction. CoRR abs/2009.05702 (2020) - [i28]Boris Ivanovic, Amine Elhafsi, Guy Rosman, Adrien Gaidon, Marco Pavone:
MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control. CoRR abs/2009.07517 (2020) - [i27]Deniz Beker, Hiroharu Kato, Mihai Morariu, Takahiro Ando, Toru Matsuoka, Wadim Kehl, Adrien Gaidon:
Monocular Differentiable Rendering for Self-Supervised 3D Object Detection. CoRR abs/2009.14524 (2020) - [i26]Haruki Nishimura, Negar Mehr, Adrien Gaidon, Mac Schwager:
RAT iLQR: A Risk Auto-Tuning Controller to Optimally Account for Stochastic Model Mismatch. CoRR abs/2010.08174 (2020) - [i25]Shinya Shiroshita, Shirou Maruyama, Daisuke Nishiyama, Mario Ynocente Castro, Karim Hamzaoui, Guy Rosman, Jonathan A. DeCastro, Kuan-Hui Lee, Adrien Gaidon:
Behaviorally Diverse Traffic Simulation via Reinforcement Learning. CoRR abs/2011.05741 (2020) - [i24]Daisuke Nishiyama, Mario Ynocente Castro, Shirou Maruyama, Shinya Shiroshita, Karim Hamzaoui, Yi Ouyang, Guy Rosman, Jonathan A. DeCastro, Kuan-Hui Lee, Adrien Gaidon:
Discovering Avoidable Planner Failures of Autonomous Vehicles using Counterfactual Analysis in Behaviorally Diverse Simulation. CoRR abs/2011.11991 (2020)
2010 – 2019
- 2019
- [c19]Vitor Guizilini, Jie Li, Rares Ambrus, Sudeep Pillai, Adrien Gaidon:
Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances. CoRL 2019: 503-512 - [c18]Rares Ambrus, Vitor Guizilini, Jie Li, Sudeep Pillai, Adrien Gaidon:
Two Stream Networks for Self-Supervised Ego-Motion Estimation. CoRL 2019: 1052-1061 - [c17]Fabian Manhardt, Wadim Kehl, Adrien Gaidon:
ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape. CVPR 2019: 2069-2078 - [c16]Felipe Codevilla, Eder Santana, Antonio M. López, Adrien Gaidon:
Exploring the Limitations of Behavior Cloning for Autonomous Driving. ICCV 2019: 9328-9337 - [c15]Kuan-Hui Lee, Germán Ros, Jie Li, Adrien Gaidon:
SPIGAN: Privileged Adversarial Learning from Simulation. ICLR (Poster) 2019 - [c14]Sudeep Pillai, Rares Ambrus, Adrien Gaidon:
SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation. ICRA 2019: 9250-9256 - [c13]Kuan-Hui Lee, Takaaki Tagawa, Jia-En M. Pan, Adrien Gaidon, Bertrand Douillard:
An Attention-based Recurrent Convolutional Network for Vehicle Taillight Recognition. IV 2019: 2365-2370 - [c12]Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma:
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. NeurIPS 2019: 1565-1576 - [i23]Felipe Codevilla, Eder Santana, Antonio M. López, Adrien Gaidon:
Exploring the Limitations of Behavior Cloning for Autonomous Driving. CoRR abs/1904.08980 (2019) - [i22]Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Adrien Gaidon:
PackNet-SfM: 3D Packing for Self-Supervised Monocular Depth Estimation. CoRR abs/1905.02693 (2019) - [i21]Kuan-Hui Lee, Takaaki Tagawa, Jia-En M. Pan, Adrien Gaidon, Bertrand Douillard:
An Attention-based Recurrent Convolutional Network for Vehicle Taillight Recognition. CoRR abs/1906.03683 (2019) - [i20]Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma:
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. CoRR abs/1906.07413 (2019) - [i19]Rares Ambrus, Vitor Guizilini, Jie Li, Sudeep Pillai, Adrien Gaidon:
Two Stream Networks for Self-Supervised Ego-Motion Estimation. CoRR abs/1910.01764 (2019) - [i18]Vitor Guizilini, Jie Li, Rares Ambrus, Sudeep Pillai, Adrien Gaidon:
Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances. CoRR abs/1910.01765 (2019) - [i17]César Roberto de Souza, Adrien Gaidon, Yohann Cabon, Naila Murray, Antonio Manuel López Peña:
Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models. CoRR abs/1910.06699 (2019) - [i16]Karttikeya Mangalam, Ehsan Adeli, Kuan-Hui Lee, Adrien Gaidon, Juan Carlos Niebles:
Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision. CoRR abs/1911.01138 (2019) - [i15]Sergey Zakharov, Wadim Kehl, Arjun Bhargava, Adrien Gaidon:
Autolabeling 3D Objects with Differentiable Rendering of SDF Shape Priors. CoRR abs/1911.11288 (2019) - [i14]Rui Hou, Jie Li, Arjun Bhargava, Allan Raventos, Vitor Guizilini, Chao Fang, Jerome P. Lynch, Adrien Gaidon:
Real-Time Panoptic Segmentation from Dense Detections. CoRR abs/1912.01202 (2019) - [i13]Jiexiong Tang, Rares Ambrus, Vitor Guizilini, Sudeep Pillai, Hanme Kim, Adrien Gaidon:
Self-Supervised 3D Keypoint Learning for Ego-motion Estimation. CoRR abs/1912.03426 (2019) - 2018
- [j3]Adrien Gaidon, Antonio M. López, Florent Perronnin:
The Reasonable Effectiveness of Synthetic Visual Data. Int. J. Comput. Vis. 126(9): 899-901 (2018) - [i12]Sudeep Pillai, Rares Ambrus, Adrien Gaidon:
SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation. CoRR abs/1810.01849 (2018) - [i11]Kuan-Hui Lee, Germán Ros, Jie Li, Adrien Gaidon:
SPIGAN: Privileged Adversarial Learning from Simulation. CoRR abs/1810.03756 (2018) - [i10]Jie Li, Allan Raventos, Arjun Bhargava, Takaaki Tagawa, Adrien Gaidon:
Learning to Fuse Things and Stuff. CoRR abs/1812.01192 (2018) - [i9]Fabian Manhardt, Wadim Kehl, Adrien Gaidon:
ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape. CoRR abs/1812.02781 (2018) - 2017
- [c11]César Roberto de Souza, Adrien Gaidon, Yohann Cabon, Antonio Manuel López Peña:
Procedural Generation of Videos to Train Deep Action Recognition Networks. CVPR 2017: 2594-2604 - 2016
- [c10]Adrien Gaidon, Qiao Wang, Yohann Cabon, Eleonora Vig:
VirtualWorlds as Proxy for Multi-object Tracking Analysis. CVPR 2016: 4340-4349 - [c9]César Roberto de Souza, Adrien Gaidon, Eleonora Vig, Antonio Manuel López Peña:
Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition. ECCV (7) 2016: 697-716 - [i8]Adrien Gaidon, Qiao Wang, Yohann Cabon, Eleonora Vig:
Virtual Worlds as Proxy for Multi-Object Tracking Analysis. CoRR abs/1605.06457 (2016) - [i7]César Roberto de Souza, Adrien Gaidon, Eleonora Vig, Antonio Manuel López Peña:
Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition. CoRR abs/1608.07138 (2016) - [i6]César Roberto de Souza, Adrien Gaidon, Yohann Cabon, Antonio Manuel López Peña:
Procedural Generation of Videos to Train Deep Action Recognition Networks. CoRR abs/1612.00881 (2016) - 2015
- [c8]Adrien Gaidon, Eleonora Vig:
Online Domain Adaptation for Multi-Object Tracking. BMVC 2015: 3.1-3.13 - [c7]Albert Gordo, Adrien Gaidon, Florent Perronnin:
Deep Fishing: Gradient Features from Deep Nets. BMVC 2015: 111.1-111.12 - [c6]Adrian Mos, Adrien Gaidon, Eleonora Vig:
Extending Generic BPM with Computer Vision Capabilities. ICSOC Workshops 2015: 103-114 - [i5]Guillaume Bouchard, Théo Trouillon, Julien Perez, Adrien Gaidon:
Accelerating Stochastic Gradient Descent via Online Learning to Sample. CoRR abs/1506.09016 (2015) - [i4]Albert Gordo, Adrien Gaidon, Florent Perronnin:
Deep Fishing: Gradient Features from Deep Nets. CoRR abs/1507.06429 (2015) - [i3]Adrien Gaidon, Eleonora Vig:
Online Domain Adaptation for Multi-Object Tracking. CoRR abs/1508.00776 (2015) - 2014
- [j2]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Activity representation with motion hierarchies. Int. J. Comput. Vis. 107(3): 219-238 (2014) - [i2]Adrien Gaidon, Gloria Zen, José A. Rodríguez-Serrano:
Self-Learning Camera: Autonomous Adaptation of Object Detectors to Unlabeled Video Streams. CoRR abs/1406.4296 (2014) - 2013
- [j1]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Temporal Localization of Actions with Actoms. IEEE Trans. Pattern Anal. Mach. Intell. 35(11): 2782-2795 (2013) - [i1]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Automatic Recognition of Human Activities in Realistic Videos. ERCIM News 2013(95) (2013) - 2012
- [c5]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Recognizing activities with cluster-trees of tracklets. BMVC 2012: 1-13 - 2011
- [c4]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
A time series kernel for action recognition. BMVC 2011: 1-11 - [c3]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Actom sequence models for efficient action detection. CVPR 2011: 3201-3208
2000 – 2009
- 2009
- [c2]Adrien Gaidon, Marcin Marszalek, Cordelia Schmid:
Mining Visual Actions from Movies. BMVC 2009: 1-11 - 2008
- [c1]Matthijs Douze, Adrien Gaidon, Hervé Jégou, Marcin Marszalek, Cordelia Schmid:
INRIA-LEAR'S Video Copy Detection System. TRECVID 2008
Coauthor Index
Rares Ambrus
aka: Rares Andrei Ambrus
aka: Rares Andrei Ambrus
[c80] [c79] [c78] [i84] [i83] [i82] [i80] [c75] [c72] [c71] [c70] [c69] [c67] [i78] [i76] [i75] [i72] [i71] [i70] [j8] [j7] [c64] [c63] [c62] [c58] [c57] [c51] [i66] [i64] [i61] [i60] [i59] [i56] [i55] [c49] [c47] [c45] [c44] [c42] [c39] [i53] [i50] [i49] [i48] [i43] [i42] [i40] [c38] [c37] [c35] [c29] [c26] [i38] [i31] [i30] [c19] [c18] [c14] [i22] [i19] [i18] [i13] [i12]
[c79] [i83] [i82] [c75] [c72] [c71] [c70] [c68] [c67] [i78] [i76] [i75] [i72] [i71] [i70] [j8] [j7] [c64] [c62] [c59] [c57] [c51] [i66] [i64] [i59] [i57] [i56] [c49] [c47] [c45] [c44] [c39] [i53] [i50] [i49] [i48] [i43] [i40] [c38] [c37] [c35] [c34] [c29] [i38] [i31] [c19] [c18] [i22] [i19] [i18] [i14] [i13]
Antonio M. López 0001
aka: Antonio Manuel López Peña
aka: Antonio Manuel López Peña
Rowan McAllister
aka: Rowan Thomas McAllister
aka: Rowan Thomas McAllister
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