Papers
Modeling Long-horizon Tasks as Sequential Interaction Landscapes
Soeren Pirk, Karol Hausman, Alexander Toshev et al.
Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation
Yu Xiang, Christopher Xie, Arsalan Mousavian et al.
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency
Mel Vecerik, Jean-Baptiste Regli, Oleg Sushkov et al.
SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation
Xingyu Lin, Yufei Wang, Jake Olkin et al.
Recovering and Simulating Pedestrians in the Wild
Ze Yang, Sivabalan Manivasagam, Ming Liang et al.
One Thousand and One Hours: Self-driving Motion Prediction Dataset
John Houston, Guido Zuidhof, Luca Bergamini et al.
Attention-Privileged Reinforcement Learning
Sasha Salter, Dushyant Rao, Markus Wulfmeier et al.
Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects
Michael Danielczuk, Ashwin Balakrishna, Daniel Brown et al.
CLOUD: Contrastive Learning of Unsupervised Dynamics
Jianren Wang, Yujie Lu, Hang Zhao
Learning Obstacle Representations for Neural Motion Planning
Robin STRUDEL, Ricardo Garcia Pinel, Justin Carpentier et al.
Reinforcement Learning with Videos: Combining Offline Observations with Interaction
Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis et al.
PLOP: Probabilistic Polynomial Objects trajectory Prediction for autonomous driving
Thibault Buhet, Emilie Wirbel, Andrei Bursuc et al.
Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents
Samyak Datta, Oleksandr Maksymets, Judy Hoffman et al.
Learning Object Manipulation Skills via Approximate State Estimation from Real Videos
Vladimír Petrík, Makarand Tapaswi, Ivan Laptev et al.
Reconfigurable Voxels: A New Representation for LiDAR-Based Point Clouds
Tai Wang, Xinge Zhu, Dahua Lin
SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving
Ming Zhou, Jun Luo, Julian Villella et al.
Task-Relevant Adversarial Imitation Learning
Konrad Zolna, Scott Reed, Alexander Novikov et al.
Action-based Representation Learning for Autonomous Driving
Yi Xiao, Felipe Codevilla, Christopher Pal et al.
GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp Detection
Kuang-Yu Jeng, Yueh-Cheng Liu, Zhe Yu Liu et al.
Positive-Unlabeled Reward Learning
Danfei Xu, Misha Denil
Accelerating Reinforcement Learning with Learned Skill Priors
Karl Pertsch, Youngwoon Lee, Joseph Lim
Fit2Form: 3D Generative Model for Robot Gripper Form Design
Huy Ha, Shubham Agrawal, Shuran Song
SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning
Albert Zhao, Tong He, Yitao Liang et al.
CoT-AMFlow: Adaptive Modulation Network with Co-Teaching Strategy for Unsupervised Optical Flow Estimation
Hengli Wang, Rui Fan, Ming Liu
Learning 3D Dynamic Scene Representations for Robot Manipulation
Zhenjia Xu, Zhanpeng He, Jiajun Wu et al.