activity
20192022
most citedJoint-task Self-supervised Learning for Temporal Correspondence

53 citations · 184 across the 18 of their papers we have counts for

collaborators

28 papers

cs.CV2021

Video Autoencoder: self-supervised disentanglement of static 3D structure and motion

Zihang Lai, Sifei Liu, Alexei A. Efros +1

A video autoencoder is proposed for learning disentan- gled representations of 3D structure and camera pose from videos in a self-supervised manner. Relying on temporal continuity…

cs.CV202111 cited

Test-Time Personalization with a Transformer for Human Pose Estimation

Yizhuo Li, Miao Hao, Zonglin Di +2

We propose to personalize a human pose estimator given a set of test images of a person without using any manual annotations. While there is a significant advancement in human pose…

cs.CV20212 cited

Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time

Shaowei Liu, Hanwen Jiang, Jiarui Xu +2

Estimating 3D hand and object pose from a single image is an extremely challenging problem: hands and objects are often self-occluded during interactions, and the 3D annotations ar…

cs.RO2021

Single RGB-D Camera Teleoperation for General Robotic Manipulation

Quan Vuong, Yuzhe Qin, Runlin Guo +3

We propose a teleoperation system that uses a single RGB-D camera as the human motion capture device. Our system can perform general manipulation tasks such as cloth folding, hamme…

cs.LG20212 cited

DAIR: Disentangled Attention Intrinsic Regularization for Safe and Efficient Bimanual Manipulation

Minghao Zhang, Pingcheng Jian, Yi Wu +2

We address the problem of safely solving complex bimanual robot manipulation tasks with sparse rewards. Such challenging tasks can be decomposed into sub-tasks that are accomplisha…

cs.CV2021

Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency

Haiping Wu, Xiaolong Wang

Recent works have advanced the performance of self-supervised representation learning by a large margin. The core among these methods is intra-image invariance learning. Two differ…