Solution for Point Tracking Task of ICCV 1st Perception Test Challenge
  2023
Hongpeng Pan Yang Yang Zhongtian Fu Yuxuan Zhang Shian Du Yi Xu Xiangyang Ji
This report proposes an improved method for the Tracking Any Point (TAP)
task, which tracks any physical surface through a video. Several existing
approaches have explored the TAP by considering the temporal relationships to
obtain smooth point motion trajectories, however, they still suffer from the
cumulative error caused by temporal prediction. To address this issue, we
propose a simple yet effective approach called TAP with confident static points
(TAPIR+), which focuses on rectifying the tracking of the static point in the
videos shot by a static camera. To clarify, our approach contains two key
components: (1) Multi-granularity Camera Motion Detection, which could identify
the video sequence by the static camera shot. (2) CMR-based point trajectory
prediction with one moving object segmentation approach to isolate the static
point from the moving object. Our approach ranked first in the final test with
a score of 0.46.