ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking | Paper Citation Record

Observation 6552ba65-d72e-4c91-9e8d-b4fa6e6a1711 · outbound

This paper cites Can visual foundation models achieve long-term point tracking?, 2024.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Can visual foundation models achieve long-term point tracking?, 2024

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.291718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 61afd7db-6732-4579-9ea3-f2f4d829830e · outbound

This paper cites Creatures great and SMAL: Recovering the shape and motion of animals from video.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Creatures great and SMAL: Recovering the shape and motion of animals from video

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.280619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 829e1384-f93d-4383-a91c-1ee6d5be502a · outbound

This paper cites High accuracy optical flow estimation based on a theory for warping.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking High accuracy optical flow estimation based on a theory for warping

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.269160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e2b30d43-bbca-4d0f-84c4-a3693418e5f0 · outbound

This paper cites Large displacement optical flow.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Large displacement optical flow

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.256962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 34cea426-105f-4b0c-b274-817db60d918c · outbound

This paper cites End-to- end object detection with transformers, 2020.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking End-to- end object detection with transformers, 2020

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.458029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7631bf1a-40c6-4fe3-8828-d102351ca42a · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Emerg- ing properties in self-supervised vision transformers

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.462104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42d8423b-cc45-43a5-acf3-711d2a3e349f · outbound

This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Quo vadis, action recognition? a new model and the kinetics dataset

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.466325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a116456-4cdb-430e-9a20-c098db9fb367 · outbound

This paper cites Zero-Shot Image Feature Consensus with Deep Functional Maps.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Zero-Shot Image Feature Consensus with Deep Functional Maps

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.470226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 413f5904-c922-4781-9f15-cf7fec1769ef · outbound

This paper cites Cats: Cost ag- gregation transformers for visual correspondence.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Cats: Cost ag- gregation transformers for visual correspondence

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.474598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2352278-d9c8-485d-b745-186ee08729b5 · outbound

This paper cites Flowtrack: Revisiting optical flow for long- range dense tracking.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Flowtrack: Revisiting optical flow for long- range dense tracking

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.220155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 19a7cdb4-0901-4151-a958-c2116eaa5d38 · outbound

This paper cites Local All-Pair Correspondence for Point Tracking.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Local All-Pair Correspondence for Point Tracking

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.482403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01488e91-2393-47a0-8104-f8aeb432eab9 · outbound

This paper cites TAP-vid: A benchmark for track- ing any point in a video.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking TAP-vid: A benchmark for track- ing any point in a video

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.208539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8f664c0f-cc24-43b3-a1cb-62b6c7af4cf7 · outbound

This paper cites Tapir: Tracking any point with per-frame initialization and temporal refinement.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Tapir: Tracking any point with per-frame initialization and temporal refinement

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.197105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dc7376dd-52a7-4a97-8836-40a355208089 · outbound

This paper cites Boot- sTAP: Bootstrapped training for tracking-any-point.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Boot- sTAP: Bootstrapped training for tracking-any-point

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.493883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64e1e4e3-dd1c-4800-b76e-04e3ae19fc1f · outbound

This paper cites Flownet: Learning optical flow with convolutional networks.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Flownet: Learning optical flow with convolutional networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.178169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3b0d7696-c491-4963-8a81-c4055c417fd9 · outbound

This paper cites Videoswap: Customized video subject swapping with interactive semantic point cor- respondence.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Videoswap: Customized video subject swapping with interactive semantic point cor- respondence

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.166278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 22ad7a30-6261-452f-8ae1-92f3b7bee192 · outbound

This paper cites Particle video revisited: Tracking through occlusions using point trajectories.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Particle video revisited: Tracking through occlusions using point trajectories

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.154768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 96c6a589-35c1-4bd8-b56e-9fd2189d6387 · outbound

This paper cites Unsupervised semantic correspondence using stable diffu- sion.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Unsupervised semantic correspondence using stable diffu- sion

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.143020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cea68c23-66fb-402d-ba66-77660ab412fe · outbound

This paper cites Determining opti- cal flow.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Determining opti- cal flow

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.511462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f6fc893-67c2-4522-93b9-190d5c69ca3e · outbound

This paper cites Flowformer: A transformer architecture for optical flow.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Flowformer: A transformer architecture for optical flow

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.123126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a632f953-5436-4eb4-89b7-892e32950300 · outbound

This paper cites Flownet 2.0: Evolu- tion of optical flow estimation with deep networks.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Flownet 2.0: Evolu- tion of optical flow estimation with deep networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.111273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5a699c15-c13d-466a-b00b-782d9ca67342 · outbound

This paper cites A new approach to linear filtering and prediction problems.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking A new approach to linear filtering and prediction problems

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.099514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0a15c0b3-b576-4899-abb9-0dbdc940db14 · outbound

This paper cites CoTracker: It is Better to Track Together.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking CoTracker: It is Better to Track Together

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.525832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c63a6cfa-4be0-46ac-9f3e-fecedbb7f969 · outbound

This paper cites CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.530028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fbb5ed4-1197-463e-b2a3-e469c67c92d4 · outbound

This paper cites Mosca: Dynamic gaussian fusion from casual videos via 4d motion scaffolds, 2024.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Mosca: Dynamic gaussian fusion from casual videos via 4d motion scaffolds, 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.087185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 75f25811-c647-4c3a-91cd-91c0b0aece9c · outbound

This paper cites TAPTRv2: Attention-based Position Update Improves Tracking Any Point.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking TAPTRv2: Attention-based Position Update Improves Tracking Any Point

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:57:28.760417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 12691d5f-affb-491c-a50c-3d243e800b7d · outbound

This paper cites Taptr: Tracking any point with transformers as detection.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Taptr: Tracking any point with transformers as detection

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.074786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 94a56658-6f1b-41d1-9477-6c070ac8401c · outbound

This paper cites Decomposition Betters Tracking Everything Everywhere.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Decomposition Betters Tracking Everything Everywhere

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:57:28.744300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5011270b-182e-45e2-bce0-a4b7cf19ccc4 · outbound

This paper cites an unresolved cited work.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:57:29.063169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation da4f8154-5ff7-4d19-8dcf-4ad4d738cce6 · outbound

This paper cites An iterative image reg- istration technique with an application to stereo vision.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking An iterative image reg- istration technique with an application to stereo vision

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.553474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c17ea15-847b-4787-90f1-e54e7dd99f8d · outbound

This paper cites Diffusion hyperfeatures: Searching through time and space for semantic correspondence.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Diffusion hyperfeatures: Searching through time and space for semantic correspondence

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.556958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff560cce-e829-48ae-a3ca-7fde7bf90171 · outbound

This paper cites Dgc-net: Dense ge- ometric correspondence network.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Dgc-net: Dense ge- ometric correspondence network

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.037186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 560ec1f2-a557-46ab-a8dc-e07b2af4a5c2 · outbound

This paper cites Mft: Long- term tracking of every pixel.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Mft: Long- term tracking of every pixel

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.026041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e75b1e65-b6f3-46af-ad13-169510a279a4 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking DINOv2: Learning Robust Visual Features without Supervision

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.567661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83a27a35-9939-4059-9945-8918940503da · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking The 2017 DAVIS Challenge on Video Object Segmentation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.571556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc9bbe00-6693-434e-82d4-2a2a43c4ec09 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Learning transferable visual models from natural language supervi- sion

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.575272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d3cfcab-9d0c-42ed-8620-cb743606e8f9 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking SAM 2: Segment Anything in Images and Videos

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.578954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44db6e24-b68e-41fc-b5ee-716affb58cc3 · outbound

This paper cites Efficient neighbourhood consensus networks via submanifold sparse convolutions.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Efficient neighbourhood consensus networks via submanifold sparse convolutions

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:29.007390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2f4f13b3-dc98-4916-8f45-a14c0a9216d8 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking High-resolution image synthesis with latent diffusion models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.586232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10da1c63-7bbb-449e-8884-5d8e344dac39 · outbound

This paper cites Towards longer long-range motion trajectories.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Towards longer long-range motion trajectories

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.988756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86d24136-1604-425d-846b-b7e82536c437 · outbound

This paper cites Orb: An efficient alternative to sift or surf.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Orb: An efficient alternative to sift or surf

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.593506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e964260-027a-4157-9794-c95024ddc4dd · outbound

This paper cites Sand and S.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Sand and S

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.970344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a5a8ce2c-237e-4be9-ae4a-42349690baf0 · outbound

This paper cites Track Everything Everywhere Fast and Robustly.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Track Everything Everywhere Fast and Robustly

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:57:28.694955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8fa16cb2-2f4f-4ec9-986d-e6677ce52d73 · outbound

This paper cites Dynamic gaussian marbles for novel view synthesis of casual monocular videos, 2024.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Dynamic gaussian marbles for novel view synthesis of casual monocular videos, 2024

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.958696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6ee8b286-1c32-4258-9cb2-5455e840d8f9 · outbound

This paper cites Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.608192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bc41159-9a32-4ab4-aef1-042a9e453a3c · outbound

This paper cites Emergent correspondence from image diffusion.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Emergent correspondence from image diffusion

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.612135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e498a09-cf55-49b6-ad6d-c46575714dbc · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Raft: Recurrent all-pairs field transforms for optical flow

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.615630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a6e8f67-8960-47ae-99f2-78f35c530aa0 · outbound

This paper cites Glu- net: Global-local universal network for dense flow and corre- spondences.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Glu- net: Global-local universal network for dense flow and corre- spondences

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:28.619344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d65f6498-8704-4e10-843e-38ae94f78954 · outbound

This paper cites Dino-tracker: Taming dino for self-supervised point tracking in a single video, 2024.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Dino-tracker: Taming dino for self-supervised point tracking in a single video, 2024

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.917577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cfa10cc6-793d-47c8-8e87-4845ce322b6d · outbound

This paper cites Tracking everything everywhere all at once.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Tracking everything everywhere all at once

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.906129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1bf003cc-cfee-43f0-a7d0-62d23b9da4a8 · outbound

This paper cites Shape of motion: 4d reconstruc- tion from a single video.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Shape of motion: 4d reconstruc- tion from a single video

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.894793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4ffbc76a-54ab-463d-9525-b1233c35393b · outbound

This paper cites Spatialtracker: Tracking any 2d pixels in 3d space.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Spatialtracker: Tracking any 2d pixels in 3d space

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.883184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f6e9f25a-192a-4aea-b7ff-1aed53b4c251 · outbound

This paper cites Telling left from right: Identifying geometry-aware semantic corre- spondence.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Telling left from right: Identifying geometry-aware semantic corre- spondence

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.871309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 641487b8-00c5-41ba-88be-0cfec4b6e505 · outbound

This paper cites an unresolved cited work.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:57:28.859084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b352dfea-1ef4-4615-96b4-85c453349ad0 · outbound

This paper cites Hyperparameters During the dual filtering stage, we apply different thresholds to predictions from flow and long-term keypoints.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking Hyperparameters During the dual filtering stage, we apply different thresholds to predictions from flow and long-term keypoints

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.848233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d694050d-94f4-47bd-89ea-7c55c20a410e · outbound

This paper cites While optical flow and geometry-aware features can be computed densely, generat- ing masks for each pixel is both time-intensive and memory- intensive.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking While optical flow and geometry-aware features can be computed densely, generat- ing masks for each pixel is both time-intensive and memory- intensive

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.835204Z

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Observation 97bfaf46-b9d4-4c75-995c-636649bf8cfd · outbound

This paper cites The total time consumed for our method includes the time for keypoint extraction, mask generation, geometry-aware feature extraction and probabilistic integration.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking The total time consumed for our method includes the time for keypoint extraction, mask generation, geometry-aware feature extraction and probabilistic integration

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.822742Z

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Observation b91ea56e-223e-4acf-aed9-50985c832994 · outbound

This paper cites We conduct experiments on more challenging cases and show the quali- tative results.

ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking We conduct experiments on more challenging cases and show the quali- tative results

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:57:28.811281Z

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