Chen Wang
@cwchenwang.bsky.social
Ph.D. student at UPenn, B.Eng and M.Eng from THU
(1/N)🚀Introducing Protracker: Inspired by Kalman filter, we tackle point tracking with a robust probabilistic approach.
🌟Our method integrates multiple predictions from both optical flow and semantic correspondences in a unified framework with probabilistic fusion.
🌟Our method integrates multiple predictions from both optical flow and semantic correspondences in a unified framework with probabilistic fusion.
January 8, 2025 at 12:54 AM
(1/N)🚀Introducing Protracker: Inspired by Kalman filter, we tackle point tracking with a robust probabilistic approach.
🌟Our method integrates multiple predictions from both optical flow and semantic correspondences in a unified framework with probabilistic fusion.
🌟Our method integrates multiple predictions from both optical flow and semantic correspondences in a unified framework with probabilistic fusion.
Reposted by Chen Wang
ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking
Tingyang Zhang, @cwchenwang.bsky.social, @frankzydou.bsky.social, Qingzhe Gao, Jiahui Lei, Baoquan Chen, @lingjieliu.bsky.social
arxiv.org/abs/2501.03220
Tingyang Zhang, @cwchenwang.bsky.social, @frankzydou.bsky.social, Qingzhe Gao, Jiahui Lei, Baoquan Chen, @lingjieliu.bsky.social
arxiv.org/abs/2501.03220
January 7, 2025 at 4:30 AM
ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking
Tingyang Zhang, @cwchenwang.bsky.social, @frankzydou.bsky.social, Qingzhe Gao, Jiahui Lei, Baoquan Chen, @lingjieliu.bsky.social
arxiv.org/abs/2501.03220
Tingyang Zhang, @cwchenwang.bsky.social, @frankzydou.bsky.social, Qingzhe Gao, Jiahui Lei, Baoquan Chen, @lingjieliu.bsky.social
arxiv.org/abs/2501.03220