TAPNet: Tracking Any Point (TAP-Vid, TAPIR, TAPNext)
Source: https://github.com/google-deepmind/tapnet
Structured fields
{
"archived": false,
"checked_at": "2026-10-17T00:00:00.000Z",
"usefulness": "Google DeepMind's point-tracking family: TAP-Vid benchmark, TAPIR, online/causal TAPIR, BootsTAP, TAPVid-3D and newer TAPNext variants, with Colabs and checkpoints. Reference for evaluating tracking quality.",
"source_type": "repository",
"availability": "available",
"dependencies": [
"JAX"
],
"source_owner": "Google DeepMind",
"next_check_at": "2026-10-24T00:00:00.000Z",
"upstream_updated_at": "2026-09-15T21:00:25.000Z"
}Evidence claims
- [upstream_claim] README links TAP-Vid, TAPIR, RoboTAP, BootsTAP, TAPVid-3D, TAPNext and TRAJAN; Colabs include Online TAPIR; achieves ~17 fps on 480x480 on a Quadro RTX 4000 per README. · locator: README header and Colab list source
- [sourced_fact] README License and Disclaimer: all software is Apache 2.0 except TAPVid-3D benchmark materials covered by tapvid3d/LICENSE. · locator: README, License and Disclaimer source
- [sourced_fact] Checkpoints are loaded from tapnet/checkpoint/ (checkpoint.npy) and are downloadable from the README or HuggingFace google/tapnet. · locator: README, checkpoints source
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| code | Apache-2.0 | permitted | permitted | permitted | unknown | Apache 2.0 except TAPVid-3D materials under tapvid3d/LICENSE (not read). |
| model_weights | unknown | unknown | unknown | unknown | unknown | Checkpoint license not separately read. |