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Point Tracking

61 papers with code · 8 benchmarks · 4 datasets archive 2025-07-28

Computer Vision

Point Tracking, often referred to as Tracking any Point (TAP) involves acquiring, focusing on, and continuously tracking specific target point/points across video frames. The system identifies the target point, maintains focus, and predicts its movement, enabling smooth tracking even if the target moves unpredictably, or through occlusions. TAP has wide applications like object tracking, surveillance, and autonomous navigation.

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

8 leaderboard tables shown for this task, 8 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

DatasetBest model (first row in archive order)PaperCodeSyntologyCompare
TAP-Vid-DAVIS (3 rows) LocoTrack-B Local All-Pair Correspondence for Point Tracking code Syntology ran 6 of 12 samples · 6 unverified Compare
PointOdyssey (2 rows) PIPs++ PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Tracking code Syntology ran 10 of 13 samples · 3 unverified Compare
TAP-Vid-DAVIS-First (2 rows) LocoTrack-B Local All-Pair Correspondence for Point Tracking code Syntology ran 6 of 12 samples · 6 unverified Compare
TAP-Vid-Kinetics (2 rows) BootsTAPIR BootsTAP: Bootstrapped Training for Tracking-Any-Point code — Compare
TAP-Vid-Kinetics-First (2 rows) LocoTrack-B Local All-Pair Correspondence for Point Tracking code Syntology ran 6 of 12 samples · 6 unverified Compare
TAP-Vid-RGB-Stacking (2 rows) BootsTAPIR BootsTAP: Bootstrapped Training for Tracking-Any-Point code — Compare
Perception Test (1 row) Static Baseline Perception Test: A Diagnostic Benchmark for Multimodal Video Models code — Compare
TAP-Vid (1 row) PIPs++ PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Tracking code Syntology ran 10 of 13 samples · 3 unverified Compare

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 61 papers with code (151 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

Syntology lines on 14 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.

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