Lune

CVPR2023Top-tier venue

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

Haojie Zhao, Junsong Chen, Lijun Wang, Huchuan Lu

2023Year
5Top-tier citations

Abstract

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.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext c111afa2-01c4-48ff-9e2a-8da5002beda7

Cited by top-tier papers5

Ask how each one uses it

Builds on17

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines