95 citations · 135 across the 6 of their papers we have counts for
7 papers
Track Anything: Segment Anything Meets Videos
Jinyu Yang, Mingqi Gao, Zhe Li +3
Recently, the Segment Anything Model (SAM) gains lots of attention rapidly due to its impressive segmentation performance on images. Regarding its strong ability on image segmentat…
Learning Dual-Fused Modality-Aware Representations for RGBD Tracking
Shang Gao, Jinyu Yang, Zhe Li +3
With the development of depth sensors in recent years, RGBD object tracking has received significant attention. Compared with the traditional RGB object tracking, the addition of t…
Prompting for Multi-Modal Tracking
Jinyu Yang, Zhe Li, Feng Zheng +2
Multi-modal tracking gains attention due to its ability to be more accurate and robust in complex scenarios compared to traditional RGB-based tracking. Its key lies in how to fuse…
RGBD Object Tracking: An In-depth Review
Jinyu Yang, Zhe Li, Song Yan +4
RGBD object tracking is gaining momentum in computer vision research thanks to the development of depth sensors. Although numerous RGBD trackers have been proposed with promising p…
Depth-only Object Tracking
Song Yan, Jinyu Yang, Ales Leonardis +1
Depth (D) indicates occlusion and is less sensitive to illumination changes, which make depth attractive modality for Visual Object Tracking (VOT). Depth is used in RGBD object tra…
DepthTrack : Unveiling the Power of RGBD Tracking
Song Yan, Jinyu Yang, Jani Käpylä +3
RGBD (RGB plus depth) object tracking is gaining momentum as RGBD sensors have become popular in many application fields such as robotics.However, the best RGBD trackers are extens…