activity
20232026
most citedDAOT: Domain-Agnostically Aligned Optimal Transport for Domain-Adaptive Crowd Counting

27 citations · 31 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

CouCE: A Unified Causal Framework for Debiased Deep Metric Learning

Xin Yuan, Zhenyang Niu, Meiqi Wan +3

Deep Metric Learning (DML) often struggles with zero-shot generalization because standard objectives inherently capture what co-occurs rather than what causes similarity. Consequen…

cs.CV2025

Neptune-X: Active X-to-Maritime Generation for Universal Maritime Object Detection

Yu Guo, Shengfeng He, Yuxu Lu +5

Maritime object detection is essential for navigation safety, surveillance, and autonomous operations, yet constrained by two key challenges: the scarcity of annotated maritime dat…

cs.CV2025

Expanding Zero-Shot Object Counting with Rich Prompts

Huilin Zhu, Senyao Li, Jingling Yuan +5

Expanding pre-trained zero-shot counting models to handle unseen categories requires more than simply adding new prompts, as this approach does not achieve the necessary alignment…

cs.CV2025

FocalCount: Towards Class-Count Imbalance in Class-Agnostic Counting

Huilin Zhu, Jingling Yuan, Zhengwei Yang +3

In class-agnostic object counting, the goal is to estimate the total number of object instances in an image without distinguishing between specific categories. Existing methods oft…

cs.CV2024

DenseTrack: Drone-based Crowd Tracking via Density-aware Motion-appearance Synergy

Yi Lei, Huilin Zhu, Jingling Yuan +3

Drone-based crowd tracking faces difficulties in accurately identifying and monitoring objects from an aerial perspective, largely due to their small size and close proximity to ea…

cs.CV2024★ 3 cited

OneRestore: A Universal Restoration Framework for Composite Degradation

Yu Guo, Yuan Gao, Yuxu Lu +3

In real-world scenarios, image impairments often manifest as composite degradations, presenting a complex interplay of elements such as low light, haze, rain, and snow. Despite thi…