collaborators

10 papers

cs.CV2026

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking

Xiangqun Zhang, Likai Wang, Zekun Qian +2

The paper introduces CD-RMOT-Bench, a benchmark for evaluating how well referring multi-object tracking models trained on one visual domain perform on different, unseen domains, an…

cs.CV2026

COVTrack++: Learning Open-Vocabulary Multi-Object Tracking from Continuous Videos via a Synergistic Paradigm

Zekun Qian, Wei Feng, Ruize Han +1

Multi-Object Tracking (MOT) has traditionally focused on a few specific categories, restricting its applicability to real-world scenarios involving diverse objects. Open-Vocabulary…

cs.CV2026

RT-SDGOD: Real-Time Single-Domain Generalized Object Detection

Yupeng Zhang, Fangzhuo Gao, Ruize Han +2

In real-world deployment under strict real-time constraints, weather and imaging variations induce significant distribution shifts, severely degrading detectors. Single-Domain Gene…

cs.CV2026

ExDet: Open-Domain Open-Vocabulary Detection with Cross-modal Extrapolation and Rectification

Yupeng Zhang, Yuzhong Feng, Ruize Han +3

Open-domain open-vocabulary detection (ODOVD) requires detectors to generalize to both novel categories and unseen domains, making it more challenging than open-vocabulary detectio…

cs.CV2026

LV-OSD: Language-Vision-Complementary Open-Set Object Detection

Yupeng Zhang, Ruize Han, Wei Feng +2

Object detection is an important task in computer vision, which aims to detect the objects of interest. through the given category list or query images. In this work, we propose a…

cs.CV2026

ODOV: Benchmark the Open-Domain Open-Vocabulary Object Detection

Yupeng Zhang, Ruize Han, Fangnan Zhou +2

Existing studies typically investigate domain shift and category shift as independent problems, however, in real-world scenarios, the two types of shifts often occur simultaneously…