activity
20192026
most citedVehicle Re-identification in Aerial Imagery: Dataset and Approach

14 citations · 30 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Beyond Appearance: A Multi-cue Framework and Large-scale Benchmark for Pedestrian Association and Tracking on Mobile Aerial-Ground Platforms

Ruiqi Wu, Bingliang Jiao, Ruize Han +6

Multi-view Multi-object Association and Tracking (MvMoAT) associates objects across camera views and tracks them over time, supporting identity persistence and forensic trajectory…

cs.CV2025

SeCap: Self-Calibrating and Adaptive Prompts for Cross-view Person Re-Identification in Aerial-Ground Networks

Shining Wang, Yunlong Wang, Ruiqi Wu +3

When discussing the Aerial-Ground Person Re-identification (AGPReID) task, we face the main challenge of the significant appearance variations caused by different viewpoints, makin…

cs.CV2024

Dynamic Textual Prompt For Rehearsal-free Lifelong Person Re-identification

Hongyu Chen, Bingliang Jiao, Wenxuan Wang +1

Lifelong person re-identification attempts to recognize people across cameras and integrate new knowledge from continuous data streams. Key challenges involve addressing catastroph…

cs.CV202413 cited

Enhancing Visible-Infrared Person Re-identification with Modality- and Instance-aware Visual Prompt Learning

Ruiqi Wu, Bingliang Jiao, Wenxuan Wang +2

The Visible-Infrared Person Re-identification (VI ReID) aims to match visible and infrared images of the same pedestrians across non-overlapped camera views. These two input modali…

cs.CV2024

Dual-Modal Prompting for Sketch-Based Image Retrieval

Liying Gao, Bingliang Jiao, Peng Wang +3

Sketch-based image retrieval (SBIR) associates hand-drawn sketches with their corresponding realistic images. In this study, we aim to tackle two major challenges of this task simu…

cs.CV20222 cited

Generalizable Person Re-Identification via Viewpoint Alignment and Fusion

Bingliang Jiao, Lingqiao Liu, Liying Gao +5

In the current person Re-identification (ReID) methods, most domain generalization works focus on dealing with style differences between domains while largely ignoring unpredictabl…