22 citations · 40 across the 10 of their papers we have counts for
10 papers
PoseBench: Benchmarking the Robustness of Pose Estimation Models under Corruptions
Sihan Ma, Jing Zhang, Qiong Cao +1
Pose estimation aims to accurately identify anatomical keypoints in humans and animals using monocular images, which is crucial for various applications such as human-machine inter…
Contact-aware Human Motion Generation from Textual Descriptions
Sihan Ma, Qiong Cao, Jing Zhang +1
This paper addresses the problem of generating 3D interactive human motion from text. Given a textual description depicting the actions of different body parts in contact with stat…
Temporal Action Localization with Enhanced Instant Discriminability
Dingfeng Shi, Qiong Cao, Yujie Zhong +4
Temporal action detection (TAD) aims to detect all action boundaries and their corresponding categories in an untrimmed video. The unclear boundaries of actions in videos often res…
GraMMaR: Ground-aware Motion Model for 3D Human Motion Reconstruction
Sihan Ma, Qiong Cao, Hongwei Yi +2
Demystifying complex human-ground interactions is essential for accurate and realistic 3D human motion reconstruction from RGB videos, as it ensures consistency between the humans…
MotionTrack: Learning Motion Predictor for Multiple Object Tracking
Changcheng Xiao, Qiong Cao, Yujie Zhong +4
Significant progress has been achieved in multi-object tracking (MOT) through the evolution of detection and re-identification (ReID) techniques. Despite these advancements, accura…
TriDet: Temporal Action Detection with Relative Boundary Modeling
Dingfeng Shi, Yujie Zhong, Qiong Cao +3
In this paper, we present a one-stage framework TriDet for temporal action detection. Existing methods often suffer from imprecise boundary predictions due to the ambiguous action…
OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System
Chao Xue, Wei Liu, Shuai Xie +25
Automated machine learning (AutoML) seeks to build ML models with minimal human effort. While considerable research has been conducted in the area of AutoML in general, aiming to t…
A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends
Jie Gui, Tuo Chen, Jing Zhang +4
Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance. However, the process of collecting and labeling such data…
Generating Holistic 3D Human Motion from Speech
Hongwei Yi, Hualin Liang, Yifei Liu +5
This work addresses the problem of generating 3D holistic body motions from human speech. Given a speech recording, we synthesize sequences of 3D body poses, hand gestures, and fac…
ReAct: Temporal Action Detection with Relational Queries
Dingfeng Shi, Yujie Zhong, Qiong Cao +4
This work aims at advancing temporal action detection (TAD) using an encoder-decoder framework with action queries, similar to DETR, which has shown great success in object detecti…