Visual Object Tracking on Multi-modal RGB-D Videos: A Review
원문 초록
The development of visual object tracking has continued for decades. Recent years, as the wide accessibility of the low-cost RGBD sensors, the task of visual object tracking on RGB-D videos has drawn much attention. Compared to conventional RGB-only tracking, the RGB-D videos can provide more information that facilitates objecting tracking in some complicated scenarios. The goal of this review is to summarize the relative knowledge of the research filed of RGB-D tracking. To be specific, we will generalize the related RGB-D tracking benchmarking datasets as well as the corresponding performance measurements. Besides, the existing RGB-D tracking methods are summarized in the paper. Moreover, we discuss the possible future direction in the field of RGB-D tracking.
함께 살펴볼 논문
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Cross-Drone Transformer Network for Robust Single Object Tracking
3D-SiamMask: Vision-Based Multi-Rotor Aerial-Vehicle Tracking for a Moving Object
Object Tracking Using Siamese Network-Based Reinforcement Learning
UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions
Mamba-FETrack V2: Revisiting State Space Model for Frame-Event based Visual Object Tracking
R1-Track: Direct Application of MLLMs to Visual Object Tracking via Reinforcement Learning
토론
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