87 citations · 141 across the 12 of their papers we have counts for
14 papers
Co-Evolution of Pose and Mesh for 3D Human Body Estimation from Video
Yingxuan You, Hong Liu, Ti Wang +3
Despite significant progress in single image-based 3D human mesh recovery, accurately and smoothly recovering 3D human motion from a video remains challenging. Existing video-based…
PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and Segmentation
Jian Zhang, Runwei Ding, Miaoju Ban +1
Visual anomaly detection is essential and commonly used for many tasks in the field of computer vision. Recent anomaly detection datasets mainly focus on industrial automated inspe…
Integrating Human Parsing and Pose Network for Human Action Recognition
Runwei Ding, Yuhang Wen, Jinfu Liu +3
Human skeletons and RGB sequences are both widely-adopted input modalities for human action recognition. However, skeletons lack appearance features and color data suffer large amo…
Edge-guided Representation Learning for Underwater Object Detection
Linhui Dai, Hong Liu, Pinhao Song +3
Underwater object detection (UOD) is crucial for marine economic development, environmental protection, and the planet's sustainable development. The main challenges of this task a…
Interweaved Graph and Attention Network for 3D Human Pose Estimation
Ti Wang, Hong Liu, Runwei Ding +3
Despite substantial progress in 3D human pose estimation from a single-view image, prior works rarely explore global and local correlations, leading to insufficient learning of hum…
GATOR: Graph-Aware Transformer with Motion-Disentangled Regression for Human Mesh Recovery from a 2D Pose
Yingxuan You, Hong Liu, Xia Li +3
3D human mesh recovery from a 2D pose plays an important role in various applications. However, it is hard for existing methods to simultaneously capture the multiple relations dur…
HTNet: Human Topology Aware Network for 3D Human Pose Estimation
Jialun Cai, Hong Liu, Runwei Ding +3
3D human pose estimation errors would propagate along the human body topology and accumulate at the end joints of limbs. Inspired by the backtracking mechanism in automatic control…
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition
Tianyu Guo, Hong Liu, Zhan Chen +3
In recent years, self-supervised representation learning for skeleton-based action recognition has been developed with the advance of contrastive learning methods. The existing con…
Weakly-supervised 3D Human Pose Estimation with Cross-view U-shaped Graph Convolutional Network
Guoliang Hua, Hong Liu, Wenhao Li +3
Although monocular 3D human pose estimation methods have made significant progress, it is far from being solved due to the inherent depth ambiguity. Instead, exploiting multi-view…
Cloth Interactive Transformer for Virtual Try-On
Bin Ren, Hao Tang, Fanyang Meng +3
The 2D image-based virtual try-on has aroused increased interest from the multimedia and computer vision fields due to its enormous commercial value. Nevertheless, most existing im…
Achieving Domain Generalization in Underwater Object Detection by Domain Mixup and Contrastive Learning
Yang Chen, Pinhao Song, Hong Liu +4
The performance of existing underwater object detection methods degrades seriously when facing domain shift caused by complicated underwater environments. Due to the limitation of…
Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation
Wenhao Li, Hong Liu, Runwei Ding +3
Despite the great progress in 3D human pose estimation from videos, it is still an open problem to take full advantage of a redundant 2D pose sequence to learn representative repre…
WQT and DG-YOLO: towards domain generalization in underwater object detection
Hong Liu, Pinhao Song, Runwei Ding
A General Underwater Object Detector (GUOD) should perform well on most of underwater circumstances. However, with limited underwater dataset, conventional object detection methods…
A Survey on 3D Skeleton-Based Action Recognition Using Learning Method
Bin Ren, Mengyuan Liu, Runwei Ding +1
3D skeleton-based action recognition (3D SAR) has gained significant attention within the computer vision community, owing to the inherent advantages offered by skeleton data. As a…