INRIA-LEAR'S Video Copy Detection System. - Matthijs Douze; Adrien Gaidon; Hervé Jégou; Marcin Marszalek; Cordelia Schmid (TRECVID, 2008)

Mining Visual Actions from Movies. - Adrien Gaidon; Marcin Marszalek; Cordelia Schmid (BMVC, 2009)

A time series kernel for action recognition. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (BMVC, 2011)

Actom sequence models for efficient action detection. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (CVPR, 2011)

Recognizing activities with cluster-trees of tracklets. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (BMVC, 2012)

Automatic Recognition of Human Activities in Realistic Videos. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (ERCIM News, 2013)

Temporal Localization of Actions with Actoms. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Self-Learning Camera: Autonomous Adaptation of Object Detectors to Unlabeled Video Streams. - Adrien Gaidon; Gloria Zen; José A. Rodríguez-Serrano (CoRR, 2014)

Activity representation with motion hierarchies. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (Int. J. Comput. Vis., 2014)

Online Domain Adaptation for Multi-Object Tracking. - Adrien Gaidon; Eleonora Vig (BMVC, 2015)

Deep Fishing: Gradient Features from Deep Nets. - Albert Gordo; Adrien Gaidon; Florent Perronnin (BMVC, 2015)

Extending Generic BPM with Computer Vision Capabilities. - Adrian Mos; Adrien Gaidon; Eleonora Vig (ICSOC Workshops, 2015)

Accelerating Stochastic Gradient Descent via Online Learning to Sample. - Guillaume Bouchard; Théo Trouillon; Julien Perez; Adrien Gaidon (CoRR, 2015)

VirtualWorlds as Proxy for Multi-object Tracking Analysis. - Adrien Gaidon; Qiao Wang; Yohann Cabon; Eleonora Vig (CVPR, 2016)

Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition. - César Roberto de Souza; Adrien Gaidon; Eleonora Vig; Antonio Manuel López Peña (ECCV (7), 2016)

Virtual Worlds as Proxy for Multi-Object Tracking Analysis. - Adrien Gaidon; Qiao Wang; Yohann Cabon; Eleonora Vig (CoRR, 2016)

Procedural Generation of Videos to Train Deep Action Recognition Networks. - César Roberto de Souza; Adrien Gaidon; Yohann Cabon; Antonio Manuel López Peña (CVPR, 2017)

Learning to Fuse Things and Stuff. - Jie Li 031; Allan Raventos; Arjun Bhargava; Takaaki Tagawa; Adrien Gaidon (CoRR, 2018)

The Reasonable Effectiveness of Synthetic Visual Data. - Adrien Gaidon; Antonio M. López 001; Florent Perronnin (Int. J. Comput. Vis., 2018)

Two Stream Networks for Self-Supervised Ego-Motion Estimation. - Rares Ambrus; Vitor Guizilini; Jie Li 031; Sudeep Pillai; Adrien Gaidon (CoRL, 2019)

Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances. - Vitor Guizilini; Jie Li 031; Rares Ambrus; Sudeep Pillai; Adrien Gaidon (CoRL, 2019)

ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape. - Fabian Manhardt; Wadim Kehl; Adrien Gaidon (CVPR, 2019)

Exploring the Limitations of Behavior Cloning for Autonomous Driving. - Felipe Codevilla; Eder Santana; Antonio M. López 001; Adrien Gaidon (ICCV, 2019)

SPIGAN: Privileged Adversarial Learning from Simulation. - Kuan-Hui Lee; Germán Ros; Jie Li 031; Adrien Gaidon (ICLR (Poster), 2019)

SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation. - Sudeep Pillai; Rares Ambrus; Adrien Gaidon (ICRA, 2019)

An Attention-based Recurrent Convolutional Network for Vehicle Taillight Recognition. - Kuan-Hui Lee; Takaaki Tagawa; Jia-En M. Pan; Adrien Gaidon; Bertrand Douillard (IV, 2019)

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. - Kaidi Cao; Colin Wei; Adrien Gaidon; Nikos Aréchiga; Tengyu Ma 001 (NeurIPS, 2019)

PackNet-SfM: 3D Packing for Self-Supervised Monocular Depth Estimation. - Vitor Guizilini; Rares Ambrus; Sudeep Pillai; Adrien Gaidon (CoRR, 2019)

Self-Supervised 3D Keypoint Learning for Ego-motion Estimation. - Jiexiong Tang; Rares Ambrus; Vitor Guizilini; Sudeep Pillai; Hanme Kim; Adrien Gaidon (CoRR, 2019)

Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion. - Igor Vasiljevic; Vitor Guizilini; Rares Ambrus; Sudeep Pillai; Wolfram Burgard; Greg Shakhnarovich; Adrien Gaidon (3DV, 2020)

MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control. - Boris Ivanovic; Amine Elhafsi; Guy Rosman; Adrien Gaidon; Marco Pavone 001 (CoRL, 2020)

Self-Supervised 3D Keypoint Learning for Ego-Motion Estimation. - Jiexiong Tang; Rares Ambrus; Vitor Guizilini; Sudeep Pillai; Hanme Kim; Patric Jensfelt; Adrien Gaidon (CoRL, 2020)

3D Packing for Self-Supervised Monocular Depth Estimation. - Vitor Guizilini; Rares Ambrus; Sudeep Pillai; Allan Raventos; Adrien Gaidon (CVPR, 2020)

Real-Time Panoptic Segmentation From Dense Detections. - Rui Hou 007; Jie Li 031; Arjun Bhargava; Allan Raventos; Vitor Guizilini; Chao Fang; Jerome P. Lynch; Adrien Gaidon (CVPR, 2020)

Spatio-Temporal Graph for Video Captioning With Knowledge Distillation. - Boxiao Pan; Haoye Cai; De-An Huang; Kuan-Hui Lee; Adrien Gaidon; Ehsan Adeli 001; Juan Carlos Niebles (CVPR, 2020)

Autolabeling 3D Objects With Differentiable Rendering of SDF Shape Priors. - Sergey Zakharov; Wadim Kehl; Arjun Bhargava; Adrien Gaidon (CVPR, 2020)

Monocular Differentiable Rendering for Self-supervised 3D Object Detection. - Deniz Beker; Hiroharu Kato; Mihai Morariu; Takahiro Ando; Toru Matsuoka; Wadim Kehl; Adrien Gaidon (ECCV (21), 2020)

It Is Not the Journey But the Destination: Endpoint Conditioned Trajectory Prediction. - Karttikeya Mangalam; Harshayu Girase; Shreyas Agarwal; Kuan-Hui Lee; Ehsan Adeli 001; Jitendra Malik; Adrien Gaidon (ECCV (2), 2020)

Semantically-Guided Representation Learning for Self-Supervised Monocular Depth. - Vitor Guizilini; Rui Hou 007; Jie Li 031; Rares Ambrus; Adrien Gaidon (ICLR, 2020)

Driving Through Ghosts: Behavioral Cloning with False Positives. - Andreas Bühler; Adrien Gaidon; Andrei Cramariuc; Rares Ambrus; Guy Rosman; Wolfram Burgard (IROS, 2020)

PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving. - Kuan-Hui Lee; Matthew Kliemann; Adrien Gaidon; Jie Li 031; Chao Fang; Sudeep Pillai; Wolfram Burgard (IROS, 2020)

Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction. - Haruki Nishimura; Boris Ivanovic; Adrien Gaidon; Marco Pavone 001; Mac Schwager (IROS, 2020)

Behaviorally Diverse Traffic Simulation via Reinforcement Learning. - Shinya Shiroshita; Shirou Maruyama; Daisuke Nishiyama; Mario Ynocente Castro; Karim Hamzaoui; Guy Rosman; Jonathan A. DeCastro; Kuan-Hui Lee; Adrien Gaidon (IROS, 2020)

Game-Theoretic Planning for Risk-Aware Interactive Agents. - Mingyu Wang 002; Negar Mehr; Adrien Gaidon; Mac Schwager (IROS, 2020)

Discovering Avoidable Planner Failures of Autonomous Vehicles using Counterfactual Analysis in Behaviorally Diverse Simulation. - Daisuke Nishiyama; Mario Ynocente Castro; Shirou Maruyama; Shinya Shiroshita; Karim Hamzaoui; Yi Ouyang; Guy Rosman; Jonathan A. DeCastro; Kuan-Hui Lee; Adrien Gaidon (ITSC, 2020)

Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. - 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; et al. (NeurIPS (Competition and Demos), 2020)

Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving. - Zhangjie Cao; Erdem Biyik; Woodrow Z. Wang; Allan Raventos; Adrien Gaidon; Guy Rosman; Dorsa Sadigh (Robotics: Science and Systems, 2020)

Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision. - Karttikeya Mangalam; Ehsan Adeli 001; Kuan-Hui Lee; Adrien Gaidon; Juan Carlos Niebles (WACV, 2020)

Differentiable Rendering: A Survey. - Hiroharu Kato; Deniz Beker; Mihai Morariu; Takahiro Ando; Toru Matsuoka; Wadim Kehl; Adrien Gaidon (CoRR, 2020)

Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models. - César Roberto de Souza; Adrien Gaidon; Yohann Cabon; Naila Murray; Antonio M. López 001 (Int. J. Comput. Vis., 2020)

Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction. - Bingbin Liu; Ehsan Adeli 001; Zhangjie Cao; Kuan-Hui Lee; Abhijeet Shenoi; Adrien Gaidon; Juan Carlos Niebles (IEEE Robotics Autom. Lett., 2020)

Single-Shot Scene Reconstruction. - Sergey Zakharov; Rares Andrei Ambrus; Vitor Guizilini; Dennis Park; Wadim Kehl; Frédo Durand; Joshua B. Tenenbaum; Vincent Sitzmann; Jiajun Wu 001; Adrien Gaidon (CoRL, 2021)

Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion. - Vitor Guizilini; Rares Ambrus; Wolfram Burgard; Adrien Gaidon (CVPR, 2021)

Hierarchical Lovasz Embeddings for Proposal-Free Panoptic Segmentation. - Tommi Kerola; Jie Li 031; Atsushi Kanehira; Yasunori Kudo; Alexis Vallet; Adrien Gaidon (CVPR, 2021)

CoCon: Cooperative-Contrastive Learning. - Nishant Rai; Ehsan Adeli 001; Kuan-Hui Lee; Adrien Gaidon; Juan Carlos Niebles (CVPR Workshops, 2021)

Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency. - Aditya Ganeshan; Alexis Vallet; Yasunori Kudo; Shin-ichi Maeda; Tommi Kerola; Rares Ambrus; Dennis Park; Adrien Gaidon (ICCV, 2021)

Geometric Unsupervised Domain Adaptation for Semantic Segmentation. - Vitor Guizilini; Jie Li 031; Rares Ambrus; Adrien Gaidon (ICCV, 2021)

Is Pseudo-Lidar needed for Monocular 3D Object detection? - Dennis Park; Rares Ambrus; Vitor Guizilini; Jie Li 031; Adrien Gaidon (ICCV, 2021)

Learning to Track with Object Permanence. - Pavel Tokmakov; Jie Li 031; Wolfram Burgard; Adrien Gaidon (ICCV, 2021)

Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization. - Kaidi Cao; Yining Chen; Junwei Lu; Nikos Aréchiga; Adrien Gaidon; Tengyu Ma 001 (ICLR, 2021)

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. - Jeff Z. HaoChen; Colin Wei; Adrien Gaidon; Tengyu Ma 001 (NeurIPS, 2021)

Monocular Depth Estimation for Soft Visuotactile Sensors. - Rares Ambrus; Vitor Guizilini; Naveen Kuppuswamy; Andrew Beaulieu; Adrien Gaidon; Alex Alspach (RoboSoft, 2021)

RAT iLQR: A Risk Auto-Tuning Controller to Optimally Account for Stochastic Model Mismatch. - Haruki Nishimura; Negar Mehr; Adrien Gaidon; Mac Schwager (IEEE Robotics Autom. Lett., 2021)

Representation Learning for Object Detection from Unlabeled Point Cloud Sequences. - Xiangru Huang; Yue Wang 041; Vitor Campanholo Guizilini; Rares Andrei Ambrus; Adrien Gaidon; Justin M. Solomon (CoRL, 2022)

RAP: Risk-Aware Prediction for Robust Planning. - Haruki Nishimura; Jean Mercat; Blake Wulfe; Rowan Thomas McAllister; Adrien Gaidon (CoRL, 2022)

ROAD: Learning an Implicit Recursive Octree Auto-Decoder to Efficiently Encode 3D Shapes. - Sergey Zakharov; Rares Andrei Ambrus; Katherine Liu; Adrien Gaidon (CoRL, 2022)

Discovering Objects that Can Move. - Zhipeng Bao; Pavel Tokmakov; Allan Jabri; Yu-Xiong Wang; Adrien Gaidon; Martial Hebert (CVPR, 2022)

Revisiting the "Video" in Video-Language Understanding. - Shyamal Buch; Cristóbal Eyzaguirre; Adrien Gaidon; Jiajun Wu 001; Li Fei-Fei 001; Juan Carlos Niebles (CVPR, 2022)

Multi-Frame Self-Supervised Depth with Transformers. - Vitor Guizilini; Rares Ambrus; Dian Chen 005; Sergey Zakharov; Adrien Gaidon (CVPR, 2022)

Depth Field Networks For Generalizable Multi-view Scene Representation. - Vitor Guizilini; Igor Vasiljevic; Jiading Fang; Rare Ambru; Greg Shakhnarovich; Matthew R. Walter; Adrien Gaidon (ECCV (32), 2022)

ShAPO: Implicit Representations for Multi-object Shape, Appearance, and Pose Optimization. - Muhammad Zubair Irshad; Sergey Zakharov; Rares Ambrus; Thomas Kollar; Zsolt Kira; Adrien Gaidon (ECCV (2), 2022)

S2Net: Stochastic Sequential Pointcloud Forecasting. - Xinshuo Weng; Junyu Nan; Kuan-Hui Lee; Rowan McAllister; Adrien Gaidon; Nicholas Rhinehart; Kris M. Kitani (ECCV (27), 2022)

Photo-realistic Neural Domain Randomization. - Sergey Zakharov; Rares Ambrus; Vitor Guizilini; Wadim Kehl; Adrien Gaidon (ECCV (25), 2022)

Self-supervised Learning is More Robust to Dataset Imbalance. - Hong Liu; Jeff Z. HaoChen; Adrien Gaidon; Tengyu Ma 001 (ICLR, 2022)

Dynamics-Aware Comparison of Learned Reward Functions. - Blake Wulfe; Logan Michael Ellis; Jean Mercat; Rowan Thomas McAllister; Adrien Gaidon (ICLR, 2022)

Object Permanence Emerges in a Random Walk along Memory. - Pavel Tokmakov; Allan Jabri; Jie Li 031; Adrien Gaidon (ICML, 2022)

Self-Supervised Camera Self-Calibration from Video. - Jiading Fang; Igor Vasiljevic; Vitor Guizilini; Rares Ambrus; Greg Shakhnarovich; Adrien Gaidon; Matthew R. Walter (ICRA, 2022)

Control-Aware Prediction Objectives for Autonomous Driving. - Rowan McAllister; Blake Wulfe; Jean Mercat; Logan Ellis; Sergey Levine; Adrien Gaidon (ICRA, 2022)

Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty. - Boris Ivanovic; Kuan-Hui Lee; Pavel Tokmakov; Blake Wulfe; Rowan McAllister; Adrien Gaidon; Marco Pavone 001 (IROS, 2022)

Dynamics-Aware Comparison of Learned Reward Functions. - Blake Wulfe; Ashwin Balakrishna; Logan Ellis; Jean Mercat; Rowan McAllister; Adrien Gaidon (CoRR, 2022)

Seeing 3D Objects in a Single Image via Self-Supervised Static-Dynamic Disentanglement. - Prafull Sharma; Ayush Tewari; Yilun Du; Sergey Zakharov; Rares Ambrus; Adrien Gaidon; William T. Freeman; Frédo Durand; Joshua B. Tenenbaum; Vincent Sitzmann (CoRR, 2022)

Depth Field Networks for Generalizable Multi-view Scene Representation. - Vitor Guizilini; Igor Vasiljevic; Jiading Fang; Rares Ambrus; Greg Shakhnarovich; Matthew R. Walter; Adrien Gaidon (CoRR, 2022)

Learning Optical Flow, Depth, and Scene Flow Without Real-World Labels. - Vitor Guizilini; Kuan-Hui Lee; Rares Ambrus; Adrien Gaidon (IEEE Robotics Autom. Lett., 2022)

Full Surround Monodepth From Multiple Cameras. - Vitor Guizilini; Igor Vasiljevic; Rares Ambrus; Greg Shakhnarovich; Adrien Gaidon (IEEE Robotics Autom. Lett., 2022)

Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? - Gunshi Gupta; Tim G. J. Rudner; Rowan Thomas McAllister; Adrien Gaidon; Yarin Gal (CLeaR, 2023)

Viewpoint Equivariance for Multi-View 3D Object Detection. - Dian Chen 005; Jie Li 031; Vitor Guizilini; Rares Ambrus; Adrien Gaidon (CVPR, 2023)

Object Discovery from Motion-Guided Tokens. - Zhipeng Bao; Pavel Tokmakov; Yu-Xiong Wang; Adrien Gaidon; Martial Hebert (CVPR, 2023)

Multi-Object Manipulation via Object-Centric Neural Scattering Functions. - Stephen Tian; Yancheng Cai; Hong-Xing Yu; Sergey Zakharov; Katherine Liu; Adrien Gaidon; Yunzhu Li; Jiajun Wu 001 (CVPR, 2023)

Breaking the "Object" in Video Object Segmentation. - Pavel Tokmakov; Jie Li 031; Adrien Gaidon (CVPR, 2023)

Towards Zero-Shot Scale-Aware Monocular Depth Estimation. - Vitor Guizilini; Igor Vasiljevic; Dian Chen 005; Rares Ambrus; Adrien Gaidon (ICCV, 2023)

DeLiRa: Self-Supervised Depth, Light, and Radiance Fields. - Vitor Guizilini; Igor Vasiljevic; Jiading Fang; Rares Ambrus; Sergey Zakharov; Vincent Sitzmann; Adrien Gaidon (ICCV, 2023)

NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes. - Muhammad Zubair Irshad; Sergey Zakharov; Katherine Liu; Vitor Guizilini; Thomas Kollar; Adrien Gaidon; Zsolt Kira; Rares Ambrus (ICCV, 2023)

Neural Groundplans: Persistent Neural Scene Representations from a Single Image. - Prafull Sharma; Ayush Tewari; Yilun Du; Sergey Zakharov; Rares Andrei Ambrus; Adrien Gaidon; William T. Freeman; Frédo Durand; Joshua B. Tenenbaum; Vincent Sitzmann (ICLR, 2023)

Depth Is All You Need for Monocular 3D Detection. - Dennis Park; Jie Li 031; Dian Chen 005; Vitor Guizilini; Adrien Gaidon (ICRA, 2023)

Robust Self-Supervised Extrinsic Self-Calibration. - Takayuki Kanai; Igor Vasiljevic; Vitor Guizilini; Adrien Gaidon; Rares Ambrus (IROS, 2023)

In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States. - Fernando Castañeda; Haruki Nishimura; Rowan Thomas McAllister; Koushil Sreenath; Adrien Gaidon (L4DC, 2023)

NeRFuser: Large-Scale Scene Representation by NeRF Fusion. - Jiading Fang; Shengjie Lin; Igor Vasiljevic; Vitor Guizilini; Rares Ambrus; Adrien Gaidon; Gregory Shakhnarovich; Matthew R. Walter (CoRR, 2023)

HomE: Homography-Equivariant Video Representation Learning. - Anirudh Sriram; Adrien Gaidon; Jiajun Wu 001; Juan Carlos Niebles; Li Fei-Fei 001; Ehsan Adeli 001 (CoRR, 2023)

Understanding Video Transformers via Universal Concept Discovery. - Matthew Kowal; Achal Dave; Rares Ambrus; Adrien Gaidon; Konstantinos G. Derpanis; Pavel Tokmakov (CVPR, 2024)

NeRF-MAE: Masked AutoEncoders for Self-supervised 3D Representation Learning for Neural Radiance Fields. - Muhammad Zubair Irshad; Sergey Zakharov; Vitor Guizilini; Adrien Gaidon; Zsolt Kira; Rares Ambrus (ECCV (88), 2024)

Zero-Shot Multi-object Scene Completion. - Shun Iwase; Katherine Liu; Vitor Guizilini; Adrien Gaidon; Kris Kitani; Rares Ambrus; Sergey Zakharov (ECCV (3), 2024)

Streaming Detection of Queried Event Start. - Cristóbal Eyzaguirre; Eric Tang; Shyamal Buch; Adrien Gaidon; Jiajun Wu 001; Juan Carlos Niebles (NeurIPS, 2024)

ReFiNe: Recursive Field Networks for Cross-Modal Multi-Scene Representation. - Sergey Zakharov; Katherine Liu; Adrien Gaidon; Rares Ambrus (SIGGRAPH (Conference Paper Track), 2024)

Zero-Shot Multi-Object Shape Completion. - Shun Iwase; Katherine Liu; Vitor Guizilini; Adrien Gaidon; Kris Kitani; Rares Ambrus; Sergey Zakharov (CoRR, 2024)

Linearizing Large Language Models. - Jean Mercat; Igor Vasiljevic; Sedrick Keh; Kushal Arora; Achal Dave; Adrien Gaidon; Thomas Kollar (CoRR, 2024)

OmniShape: Zero-Shot Multi-Hypothesis Shape and Pose Estimation in the Real World. - Katherine Liu; Sergey Zakharov; Dian Chen 005; Takuya Ikeda; Greg Shakhnarovich; Adrien Gaidon; Rares Ambrus (CoRR, 2025)