activity
20162025
most citedLearning Deep Context-aware Features over Body and Latent Parts for Person Re-identification

90 citations · 158 across the 7 of their papers we have counts for

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9 papers · 1 filter

cs.CV2025

VS-LLM: Visual-Semantic Depression Assessment based on LLM for Drawing Projection Test

Meiqi Wu, Yaxuan Kang, Xuchen Li +5

The Drawing Projection Test (DPT) is an essential tool in art therapy, allowing psychologists to assess participants' mental states through their sketches. Specifically, through sk…

cs.CV2025

ATCTrack: Aligning Target-Context Cues with Dynamic Target States for Robust Vision-Language Tracking

X. Feng, S. Hu, X. Li +5

Vision-language tracking aims to locate the target object in the video sequence using a template patch and a language description provided in the initial frame. To achieve robust t…

cs.CV2024

Enhancing Vision-Language Tracking by Effectively Converting Textual Cues into Visual Cues

X. Feng, D. Zhang, S. Hu +5

Vision-Language Tracking (VLT) aims to localize a target in video sequences using a visual template and language description. While textual cues enhance tracking potential, current…

cs.CV20222 cited

Learning Disentangled Label Representations for Multi-label Classification

Jian Jia, Fei He, Naiyu Gao +2

Although various methods have been proposed for multi-label classification, most approaches still follow the feature learning mechanism of the single-label (multi-class) classifica…

cs.CV20211 cited

Spatial and Semantic Consistency Regularizations for Pedestrian Attribute Recognition

Jian Jia, Xiaotang Chen, Kaiqi Huang

While recent studies on pedestrian attribute recognition have shown remarkable progress in leveraging complicated networks and attention mechanisms, most of them neglect the inter-…

cs.CV202030 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…