7 citations · 7 across the 4 of their papers we have counts for
8 papers · 1 filter
Rethinking Two-Stage Referring-by-Tracking in Referring Multi-Object Tracking: Make it Strong Again
Weize Li, Yunhao Du, Qixiang Yin +2
Referring Multi-Object Tracking (RMOT) aims to track multiple objects specified by natural language expressions in videos. With the recent significant progress of one-stage methods…
Hierarchical IoU Tracking based on Interval
Yunhao Du, Zhicheng Zhao, Fei Su
Multi-Object Tracking (MOT) aims to detect and associate all targets of given classes across frames. Current dominant solutions, e.g. ByteTrack and StrongSORT++, follow the hybrid…
YYDS: Visible-Infrared Person Re-Identification with Coarse Descriptions
Yunhao Du, Zhicheng Zhao, Fei Su
Visible-infrared person re-identification (VI-ReID) is challenging due to considerable cross-modality discrepancies. Existing works mainly focus on learning modality-invariant feat…
iKUN: Speak to Trackers without Retraining
Yunhao Du, Cheng Lei, Zhicheng Zhao +1
Referring multi-object tracking (RMOT) aims to track multiple objects based on input textual descriptions. Previous works realize it by simply integrating an extra textual module i…
Video-based Visible-Infrared Person Re-Identification with Auxiliary Samples
Yunhao Du, Cheng Lei, Zhicheng Zhao +2
Visible-infrared person re-identification (VI-ReID) aims to match persons captured by visible and infrared cameras, allowing person retrieval and tracking in 24-hour surveillance s…
OMG: Observe Multiple Granularities for Natural Language-Based Vehicle Retrieval
Yunhao Du, Binyu Zhang, Xiangning Ruan +3
Retrieving tracked-vehicles by natural language descriptions plays a critical role in smart city construction. It aims to find the best match for the given texts from a set of trac…