19 citations · 36 across the 7 of their papers we have counts for
7 papers
ChartDETR: A Multi-shape Detection Network for Visual Chart Recognition
Wenyuan Xue, Dapeng Chen, Baosheng Yu +3
Visual chart recognition systems are gaining increasing attention due to the growing demand for automatically identifying table headers and values from chart images. Current method…
Video Action Recognition with Attentive Semantic Units
Yifei Chen, Dapeng Chen, Ruijin Liu +2
Visual-Language Models (VLMs) have significantly advanced action video recognition. Supervised by the semantics of action labels, recent works adapt the visual branch of VLMs to le…
PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation
Haoyu Ma, Zhe Wang, Yifei Chen +6
Recently, the vision transformer and its variants have played an increasingly important role in both monocular and multi-view human pose estimation. Considering image patches as to…
Rotation-invariant Mixed Graphical Model Network for 2D Hand Pose Estimation
Deying Kong, Haoyu Ma, Yifei Chen +1
In this paper, we propose a new architecture named Rotation-invariant Mixed Graphical Model Network (R-MGMN) to solve the problem of 2D hand pose estimation from a monocular RGB im…
Nonparametric Structure Regularization Machine for 2D Hand Pose Estimation
Yifei Chen, Haoyu Ma, Deying Kong +4
Hand pose estimation is more challenging than body pose estimation due to severe articulation, self-occlusion and high dexterity of the hand. Current approaches often rely on a pop…
Adaptive Graphical Model Network for 2D Handpose Estimation
Deying Kong, Yifei Chen, Haoyu Ma +2
In this paper, we propose a new architecture called Adaptive Graphical Model Network (AGMN) to tackle the task of 2D hand pose estimation from a monocular RGB image. The AGMN consi…
Efficient Latent Variable Graphical Model Selection via Split Bregman Method
Gui-Bo Ye, Yuanfeng Wang, Yifei Chen +1
We consider the problem of covariance matrix estimation in the presence of latent variables. Under suitable conditions, it is possible to learn the marginal covariance matrix of th…