ARKitTrack: A New Diverse Dataset for Tracking Using Mobile RGB-D Data

Haojie Zhao; Junsong Chen; Lijun Wang; Huchuan Lu

doi:10.1109/cvpr52729.2023.00496

CVPR2023顶会

ARKitTrack: A New Diverse Dataset for Tracking Using Mobile RGB-D Data

Haojie Zhao, Junsong Chen, Lijun Wang, Huchuan Lu

DOI 出版方

2023年份

5顶会引用

摘要

Figure 1 . Samples from ARKitTrack. We capture both indoor and outdoor sequences (1st row) in many scenes, including zoo, market, office, square, corridor, etc. Lots of scenarios are presented in our dataset, e.g., low or high light conditions (2nd row), surrounding clutter (3rd row), out-of-plane rotation, motion blur, deformation, etc. (4th row). Besides, we annotate each frame with object masks.