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20122021
most citedChannel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition

52 citations · 164 across the 13 of their papers we have counts for

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cs.CV2021

SDTP: Semantic-aware Decoupled Transformer Pyramid for Dense Image Prediction

Zekun Li, Yufan Liu, Bing Li +3

Although transformer has achieved great progress on computer vision tasks, the scale variation in dense image prediction is still the key challenge. Few effective multi-scale techn…

cs.CV202152 cited

Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition

Yuxin Chen, Ziqi Zhang, Chunfeng Yuan +3

Graph convolutional networks (GCNs) have been widely used and achieved remarkable results in skeleton-based action recognition. In GCNs, graph topology dominates feature aggregatio…

cs.CV202112 cited

Learn to Match: Automatic Matching Network Design for Visual Tracking

Zhipeng Zhang, Yihao Liu, Xiao Wang +2

Siamese tracking has achieved groundbreaking performance in recent years, where the essence is the efficient matching operator cross-correlation and its variants. Besides the remar…

cs.CV2021

A Simple and Strong Baseline for Universal Targeted Attacks on Siamese Visual Tracking

Zhenbang Li, Yaya Shi, Jin Gao +4

Siamese trackers are shown to be vulnerable to adversarial attacks recently. However, the existing attack methods craft the perturbations for each video independently, which comes…

cs.CV202114 cited

Learning to Predict Salient Faces: A Novel Visual-Audio Saliency Model

Yufan Liu, Minglang Qiao, Mai Xu +3

Recently, video streams have occupied a large proportion of Internet traffic, most of which contain human faces. Hence, it is necessary to predict saliency on multiple-face videos,…

cs.CV20218 cited

Open-book Video Captioning with Retrieve-Copy-Generate Network

Ziqi Zhang, Zhongang Qi, Chunfeng Yuan +4

Due to the rapid emergence of short videos and the requirement for content understanding and creation, the video captioning task has received increasing attention in recent years.…