activity
20182023
most citedEANet: Enhancing Alignment for Cross-Domain Person Re-identification

35 citations · 67 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

Cross-view Semantic Alignment for Livestreaming Product Recognition

Wenjie Yang, Yiyi Chen, Yan Li +4

Live commerce is the act of selling products online through live streaming. The customer's diverse demands for online products introduce more challenges to Livestreaming Product Re…

cs.CV2023★ 1 cited

Cross-Domain Product Representation Learning for Rich-Content E-Commerce

Xuehan Bai, Yan Li, Yanhua Cheng +3

The proliferation of short video and live-streaming platforms has revolutionized how consumers engage in online shopping. Instead of browsing product pages, consumers are now turni…

cs.CV2021

Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic Perspective

Yuxi Li, Ning Xu, Wenjie Yang +2

Modern video object segmentation (VOS) algorithms have achieved remarkably high performance in a sequential processing order, while most of currently prevailing pipelines still sho…

cs.CV2021★ 1 cited

Unveiling personnel movement in a larger indoor area with a non-overlapping multi-camera system

Ping Zhang, Zhenxiang Tao, Wenjie Yang +5

Surveillance cameras are widely applied for indoor occupancy measurement and human movement perception, which benefit for building energy management and social security. To address…

cs.CV2020★ 30 cited

Rethinking of Pedestrian Attribute Recognition: Realistic Datasets with Efficient Method

Jian Jia, Houjing Huang, Wenjie Yang +2

Despite various methods are proposed to make progress in pedestrian attribute recognition, a crucial problem on existing datasets is often neglected, namely, a large number of iden…

cs.CV2018★ 35 cited

EANet: Enhancing Alignment for Cross-Domain Person Re-identification

Houjing Huang, Wenjie Yang, Xiaotang Chen +5

Person re-identification (ReID) has achieved significant improvement under the single-domain setting. However, directly exploiting a model to new domains is always faced with huge…