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Paper Citation Record · LEDGER

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

As of 15 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 30 inbound Pith citation observations for arXiv:2411.11922.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.11922 v2

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:46:30.792409Z

measured 84 of 84 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:48:54.119308Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

54 of 54 outbound references displayed

  • verified exact0
  • verified fuzzy30
  • unresolved24
  • parse uncertain0
  • malformed identifier0
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External citation measurements

10
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 91ffa0ae-0f9c-4984-b9c7-5302470e8b4e · outbound

This paper cites BoT-SORT: Robust Associations Multi-Pedestrian Tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory BoT-SORT: Robust Associations Multi-Pedestrian Tracking

Reference 1

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Observation 8c80b3f8-fe0d-468d-83b4-76c20b7ea4c3 · outbound

This paper cites Tracking without bells and whistles.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Tracking without bells and whistles

Reference 2

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 858e4c78-01aa-411b-b37a-09867b54e797 · outbound

This paper cites Hiptrack: Visual tracking with historical prompts.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Hiptrack: Visual tracking with historical prompts

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 04d36769-13c6-424b-8912-5449e5ba5995 · outbound

This paper cites Robust object modeling for visual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Robust object modeling for visual tracking

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e5350755-1508-4897-84f7-b4f0b85ed752 · outbound

This paper cites Observation-centric sort: Rethink- ing sort for robust multi-object tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Observation-centric sort: Rethink- ing sort for robust multi-object tracking

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 22104a46-4a47-445e-9f14-a85cc8c6a6ee · outbound

This paper cites Stable- video: Text-driven consistency-aware diffusion video edit- ing.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Stable- video: Text-driven consistency-aware diffusion video edit- ing

Reference 6

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source=pdf_text observed=2026-08-12T18:46:30.222153Z digest=sha256:5015edbad69326f3184323cb59fc868f0b1d52f94052e74f78d358bd4befaf46

Observation b2c41478-032f-491a-9901-03bd4df7a710 · outbound

This paper cites AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark

Reference 7

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source=pdf_text observed=2026-08-12T18:46:30.236866Z digest=sha256:35c796ac2db8fe9f7309abb732f0ec3eaaa98aec35ef23b905a8dd411d0dfa74

Observation 4a022fbf-9346-47ce-8563-19edeb92a608 · outbound

This paper cites Transformer tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Transformer tracking

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c14a1683-58dd-473f-8f27-e7c273f90825 · outbound

This paper cites Seqtrack: Sequence to sequence learning for visual ob- ject tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Seqtrack: Sequence to sequence learning for visual ob- ject tracking

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4ab30e7f-d1ff-49a0-aee5-cc11b98a34d4 · outbound

This paper cites Siamese box adaptive network for visual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Siamese box adaptive network for visual tracking

Reference 10

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source=pdf_text observed=2026-08-12T18:46:30.279875Z digest=sha256:36212a912695c06950b94221a593ade1315078bbef7c2110760acf379f6ede2a

Observation 442d43e2-e3f4-4725-956b-03a13dc01b7d · outbound

This paper cites Tracking anything with decoupled video segmentation.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Tracking anything with decoupled video segmentation

Reference 11

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source=pdf_text observed=2026-08-12T18:46:30.287342Z digest=sha256:00debcd048c4d212d40611eb5e5d3b341ab20b2a4d41b6e29016f3e27dd583ab

Observation 3b4b425f-c430-4403-b664-c07e330f7150 · outbound

This paper cites Mixformer: End-to-end tracking with iterative mixed atten- tion.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Mixformer: End-to-end tracking with iterative mixed atten- tion

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 854b40b2-6cb6-4306-b59c-a716014e007e · outbound

This paper cites Prob- abilistic regression for visual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Prob- abilistic regression for visual tracking

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 608db237-f074-4535-a872-bd6442443ba7 · outbound

This paper cites SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

Reference 14

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Observation cb46fc39-91f2-45ce-9065-0d5eb86c86e4 · outbound

This paper cites Giaotracker: A compre- hensive framework for mcmot with global information and optimizing strategies in visdrone 2021.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Giaotracker: A compre- hensive framework for mcmot with global information and optimizing strategies in visdrone 2021

Reference 15

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 91d69408-da1b-46c2-acf5-54248de8ea2a · outbound

This paper cites Lasot: A high-quality benchmark for large-scale single ob- ject tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Lasot: A high-quality benchmark for large-scale single ob- ject tracking

Reference 16

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Observation 4eea48d4-47f1-4359-9227-80f542960260 · outbound

This paper cites Lasot: A high-quality large-scale single object tracking benchmark.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Lasot: A high-quality large-scale single object tracking benchmark

Reference 17

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 15f54103-3439-4d09-92e3-d36fca7bc5ea · outbound

This paper cites Stmtrack: Template-free visual tracking with space-time memory networks.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Stmtrack: Template-free visual tracking with space-time memory networks

Reference 18

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Observation 16871faa-c6ee-44f6-a495-77a7ffa224b0 · outbound

This paper cites Aiatrack: Attention in attention for trans- former visual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Aiatrack: Attention in attention for trans- former visual tracking

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 56a04c45-df49-4240-9493-ae8d3df83875 · outbound

This paper cites Generalized relation modeling for transformer tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Generalized relation modeling for transformer tracking

Reference 20

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fb077535-6b55-4e86-8275-a6bde90f9354 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 21

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Observation 19342456-a619-494e-a94e-912844860ca9 · outbound

This paper cites MambaMOT: State-Space Model as Motion Predictor for Multi-Object Tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory MambaMOT: State-Space Model as Motion Predictor for Multi-Object Tracking

Reference 22

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Observation b32bbd58-30c3-4c76-8ac4-0723235adae3 · outbound

This paper cites Got-10k: A large high-diversity benchmark for generic object tracking in the wild.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Got-10k: A large high-diversity benchmark for generic object tracking in the wild

Reference 23

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 080e0503-fa91-48fd-9e7d-160fbc36ff99 · outbound

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

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory A new approach to linear filtering and prediction problems

Reference 24

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Observation 685bd3db-0e78-43a2-8ee8-cd5f44740599 · outbound

This paper cites Need for speed: A bench- mark for higher frame rate object tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Need for speed: A bench- mark for higher frame rate object tracking

Reference 25

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 86ed7b79-bfe4-4976-a1b4-47c12185864d · outbound

This paper cites Segment any- thing.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Segment any- thing

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f399852c-396a-4aed-b458-7aa0a60f6f6f · outbound

This paper cites Siamrpn++: Evolution of siamese vi- sual tracking with very deep networks.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Siamrpn++: Evolution of siamese vi- sual tracking with very deep networks

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7b4627a3-7653-4a44-ad70-1dc64eff7c5a · outbound

This paper cites Swintrack: A simple and strong baseline for trans- former tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Swintrack: A simple and strong baseline for trans- former tracking

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ea6e76ea-9c12-4bb2-881b-b8566581f745 · outbound

This paper cites Tracking meets lora: Faster training, larger model, stronger performance.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Tracking meets lora: Faster training, larger model, stronger performance

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.515072Z digest=sha256:152715e40d014d06ee62138ec6a62e80e9907ce3a56cd8ceb0be8c22aead883d

Observation bdffd950-d2e5-4855-a2d0-497d83d25d7c · outbound

This paper cites Segment anything in medical images.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Segment anything in medical images

Reference 30

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Observation feacbe6a-2152-4bcc-863b-6165d02873df · outbound

This paper cites Learning target candidate association to keep track of what not to track.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Learning target candidate association to keep track of what not to track

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2fd20065-c58d-4908-9953-4290bc797c56 · outbound

This paper cites Beyond sot: Tracking multiple generic objects at once.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Beyond sot: Tracking multiple generic objects at once

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cd062c5b-d8e9-4e18-929a-f55ec99de35a · outbound

This paper cites Trackingnet: A large-scale dataset and benchmark for object tracking in the wild.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Trackingnet: A large-scale dataset and benchmark for object tracking in the wild

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:46:30.561596Z digest=sha256:860ba45759fa98feaadc172abb98c6cd1e0eec01e5ddd9f0f8db467f1e534c26

Observation 68dcd2d3-bcf8-4131-8f28-9c038c9003ff · outbound

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

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory SAM 2: Segment Anything in Images and Videos

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5516b550-ddda-4085-8b24-e731c97d01ba · outbound

This paper cites The visual object track- ing vot2016 challenge results.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory The visual object track- ing vot2016 challenge results

Reference 36

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.593017Z digest=sha256:1f5dd7b454d384858b11127c6ee2b2123b3cdb4fb9bff139fd6c65cd653e2d05

Observation b05ff1f5-f932-498a-b75e-340dc1ec8e9e · outbound

This paper cites Explicit visual prompts for visual object tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Explicit visual prompts for visual object tracking

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.601717Z digest=sha256:ee82aac7617d29ffa61813d42aa87c64057d5f899880acf942e94ff585d90110

Observation e177365a-ae87-4031-bc54-67e0257de26b · outbound

This paper cites Moviechat: From dense token to sparse memory for long video understanding.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Moviechat: From dense token to sparse memory for long video understanding

Reference 38

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source=pdf_text observed=2026-08-12T18:46:30.618151Z digest=sha256:27ca58ecd301c0b9927efe26935696dcf6672f7675734c924e8a682c0b4148c5

Observation 58efed60-9c42-4c88-8dcb-34eebf9ef1ea · outbound

This paper cites MovieChat+: Question-aware Sparse Memory for Long Video Question Answering.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory MovieChat+: Question-aware Sparse Memory for Long Video Question Answering

Reference 39

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source=pdf_text observed=2026-08-12T18:46:30.629868Z digest=sha256:e388ec12c0a2c3e9e9df849dfc7eba82a7bdf968204b74e18ff6ada21534b76e

Observation 29e1da98-c15c-4359-9d73-84c936506172 · outbound

This paper cites Attention is all you need.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Attention is all you need

Reference 40

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source=pdf_text observed=2026-08-12T18:46:30.638594Z digest=sha256:fd5f4bc23daa524e2b4ef771853e713c19a8bb0cdad6d2c8a9838d67c78b346e

Observation 8ada8d19-6643-4b2e-86cd-0c976c4fb656 · outbound

This paper cites Autoregressive visual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Autoregressive visual tracking

Reference 41

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.651020Z digest=sha256:8f17c8598f195e56ada780acd54f732d98e77ef5ec3de02c500c577136a711eb

Observation 7f246e81-df81-4a68-9264-8ada4e48dd1e · outbound

This paper cites Object track- ing benchmark.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Object track- ing benchmark

Reference 42

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source=pdf_text observed=2026-08-12T18:46:30.657783Z digest=sha256:c4f3cca932c116e445f5b819d276db33d29951e189daf58bb52ccbf1678bb8d6

Observation cbce347a-14ca-4ef1-a2c5-d02576546b3f · outbound

This paper cites Motiontrack: Learning motion predictor for multiple object tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Motiontrack: Learning motion predictor for multiple object tracking

Reference 43

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raw_fallback, observed 2026-08-12T18:46:31.613123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.663995Z digest=sha256:7c349ed0597f71bff65a2bde3e0bdec082fb652acebb7fbd7fe5558e03c19362

Observation 3599fde3-0cca-4f3c-9590-5be2752b9e21 · outbound

This paper cites Autore- gressive queries for adaptive tracking with spatio-temporal transformers.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Autore- gressive queries for adaptive tracking with spatio-temporal transformers

Reference 44

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T18:46:30.672059Z digest=sha256:5a1a70d8490242b6dbb3bafcc03d7f030bcf2299700999213cc6207f89dc5ae2

Observation 4a16dae4-76cb-4e59-bb2c-4bc35bf8c802 · outbound

This paper cites Efficientsam: Leveraged masked image pretraining for efficient segment anything.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Efficientsam: Leveraged masked image pretraining for efficient segment anything

Reference 45

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source=pdf_text observed=2026-08-12T18:46:30.681340Z digest=sha256:85abd588ae4eca22ff0efcfb041922b13717537740290bac436ada7791f4ead4

Observation cb196c12-ef64-49c3-a531-2068c5aec9e4 · outbound

This paper cites YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark

Reference 46

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T18:46:30.690809Z digest=sha256:a97762e32df7c6754cdf2b3ce9fe512670ffa0366531bdc1ff9d62800995e997

Observation 6b4ff320-2f41-48e3-ac9b-e6c9b9c6f27c · outbound

This paper cites Learning spatio-temporal transformer for vi- sual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Learning spatio-temporal transformer for vi- sual tracking

Reference 47

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source=pdf_text observed=2026-08-12T18:46:30.700288Z digest=sha256:3462aa64013e689e029a8f9e957093edc5521b4517dcc40d1060d2be50ea2da3

Observation b7fe641c-5fd0-4cf2-88ec-6898e6f17b39 · outbound

This paper cites Learning spatio-temporal transformer for vi- sual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Learning spatio-temporal transformer for vi- sual tracking

Reference 48

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.709319Z digest=sha256:cfd7ba33f46e4275bf16b38900729d1613fbcb5232fddb5b49086f98d0ed19e6

Observation ebc33f02-0446-4a73-a56b-8fe7bf9efd33 · outbound

This paper cites Learning dynamic mem- ory networks for object tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Learning dynamic mem- ory networks for object tracking

Reference 49

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source=pdf_text observed=2026-08-12T18:46:30.723725Z digest=sha256:7cbf6c2e21291097187b647b647c18fe739328814315e39ceab1efae08fb2aaf

Observation eb970f7b-a2f2-4e3a-873b-5735cce8dddd · outbound

This paper cites Joint feature learning and relation modeling for tracking: A one-stream framework.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Joint feature learning and relation modeling for tracking: A one-stream framework

Reference 50

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.738426Z digest=sha256:bf062ca03e5daa4324f7f65893fd2923af4a161a4af69eafc1fe15c87bcd8823

Observation bf904cad-1266-4269-b3f6-85b74b8e9363 · outbound

This paper cites Bytetrack: Multi-object tracking by associating every 10 detection box.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Bytetrack: Multi-object tracking by associating every 10 detection box

Reference 51

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raw_fallback, observed 2026-08-12T18:46:31.402987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.749094Z digest=sha256:422c767a18ed16a4eac53c17c3c145f72bd2abfa11c144f5dbf8f11c30411259

Observation ba92a67d-f112-4a88-9971-a3a40e9b8c0b · outbound

This paper cites Deeper and wider siamese networks for real-time visual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Deeper and wider siamese networks for real-time visual tracking

Reference 52

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raw_fallback, observed 2026-08-12T18:46:31.359346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.755852Z digest=sha256:913548c00b89b3dea0985220ff8dad2626df3dabac67788c8de829748eb49e1f

Observation f1a211cd-8ffc-4fda-98fe-c58246dfadfd · outbound

This paper cites Learn to match: Automatic matching network design for visual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Learn to match: Automatic matching network design for visual tracking

Reference 53

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raw_fallback, observed 2026-08-12T18:46:31.319567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.766887Z digest=sha256:f603097d24a57bd378250d235abd85a88e1427f3b0fe02f0a0f6927d459cd806

Observation 8fb7c770-2499-459e-b1eb-8b782e828946 · outbound

This paper cites Fast Segment Anything.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Fast Segment Anything

Reference 54

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source=pdf_text observed=2026-08-12T18:46:30.778311Z digest=sha256:f95ad1cd3bd6af09de3adf4667dea0d7ff6d425d9e94c17b97fc1d53ee6957c1

Observation c908bb29-5eb5-4dd2-95f4-9a586751d58d · outbound

This paper cites Odtrack: Online dense temporal token learning for visual tracking.

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory Odtrack: Online dense temporal token learning for visual tracking

Reference 55

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raw_fallback, observed 2026-08-12T18:46:31.280513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:46:30.792409Z digest=sha256:e44ed434b4096a5c93be28753f84dc79c5a2289b63c1d9a4281cf281cb039e50

Pith citing papers

Observation da4e73e3-458a-45c6-8803-b4be9fb34104 · inbound

A Distractor-Aware Memory for Visual Object Tracking with SAM2 cites this paper.

A Distractor-Aware Memory for Visual Object Tracking with SAM2 SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 45

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source=pdf_text observed=2026-08-12T12:03:19.900284Z digest=sha256:c6f69576469436aaafe09102053435c6ddb2c3d64878f59b527dbe98591e2f7b

Observation a92f35d3-ae2c-4429-801b-e2b335a821d2 · inbound

Object Tracking in a $360^o$ View: A Novel Perspective on Bridging the Gap to Biomedical Advancements cites this paper.

Object Tracking in a $360^o$ View: A Novel Perspective on Bridging the Gap to Biomedical Advancements SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 255

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source=pdf_text observed=2026-08-12T04:45:41.439205Z digest=sha256:3d315758092eb41c2e295c646599a819fa35a522cfe2003113ddbfb93152c1ab

Observation df69cfb1-c9d2-454f-90be-7110b3926b06 · inbound

Cosmos World Foundation Model Platform for Physical AI cites this paper.

Cosmos World Foundation Model Platform for Physical AI SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 230

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arxiv_id, observed 2026-05-10T23:38:46.101259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T23:38:44.933410Z digest=sha256:0b134394cef825525c05101279c18d9b8f0520b4b81c88f57b882869c45467d8

Observation f8436d76-6eb0-4746-bec4-920f0928f311 · inbound

DanceTogether! Identity-Preserving Multi-Person Interactive Video Generation cites this paper.

DanceTogether! Identity-Preserving Multi-Person Interactive Video Generation SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 103

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source=pdf_text observed=2026-08-07T14:39:40.832814Z digest=sha256:c53dad51611209d7056dca45c0e915eaea6043a3fd9e1d1428af068688a7d2c2

Observation 592e8db7-16a2-4b95-bf0e-0fa687f063f1 · inbound

Adapting SAM 2 for Visual Object Tracking: 1st Place Solution for MMVPR Challenge Multi-Modal Tracking cites this paper.

Adapting SAM 2 for Visual Object Tracking: 1st Place Solution for MMVPR Challenge Multi-Modal Tracking SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 15

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:38:36.620001Z digest=sha256:2f2f6f42520f93e55d5d388e2d8003c392d406db76bc4ef8063c65a5cba10e91

Observation 1f06af49-3be1-4c6d-b98c-c8c3f86b6ab7 · inbound

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation cites this paper.

THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 23

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:53:10.440098Z digest=sha256:b044d93ad42931e3a699c3506f45210b7fada55dbc7a31421f89e63638ed920a

Observation 8156ef08-446b-4bc4-b78f-8e24574392c4 · inbound

A Survey on Vision-Language-Action Models: An Action Tokenization Perspective cites this paper.

A Survey on Vision-Language-Action Models: An Action Tokenization Perspective SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 91

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arxiv_id, observed 2026-05-17T14:08:35.529271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-17T14:08:34.893876Z digest=sha256:edddeec6eef1d8a411e3f018755b319556f42ebc52b3de6680e239f49c786f04

Observation 91865441-40b6-4d31-815a-8430882d1fca · inbound

HiM2SAM: Enhancing SAM2 with Hierarchical Motion Estimation and Memory Optimization towards Long-term Tracking cites this paper.

HiM2SAM: Enhancing SAM2 with Hierarchical Motion Estimation and Memory Optimization towards Long-term Tracking SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 32

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source=pdf_text observed=2026-08-06T18:41:08.260277Z digest=sha256:2ec5bc28705590666d6a674f87f64be5a4f9c51af476964f13f037fd3ed9a6dc

Observation 96fa4e76-1556-4046-93ce-99abd5080994 · inbound

SAM2RL: Towards Reinforcement Learning Memory Control in Segment Anything Model 2 cites this paper.

SAM2RL: Towards Reinforcement Learning Memory Control in Segment Anything Model 2 SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 10

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source=arxiv_source observed=2026-08-06T18:22:03.534727Z digest=sha256:1501f87b6ff6e122bea8e2fa7f6744651ffcb2b36fc284c3f496c57abe8a4b01

Observation 0143ceaf-ac61-41b2-b013-670b1c30be19 · inbound

BleedOrigin: Dynamic Bleeding Source Localization in Endoscopic Submucosal Dissection via Dual-Stage Detection and Tracking cites this paper.

BleedOrigin: Dynamic Bleeding Source Localization in Endoscopic Submucosal Dissection via Dual-Stage Detection and Tracking SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 73

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source=pdf_text observed=2026-08-06T15:46:27.716355Z digest=sha256:27343c13f4299c30877ce7268e5d6f91ddb976d1eaf07b16b8c844c13e04c9c7

Observation 5fec0903-9c14-401e-a7e2-c2fc984aa0c4 · inbound

Is Tracking really more challenging in First Person Egocentric Vision? cites this paper.

Is Tracking really more challenging in First Person Egocentric Vision? SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 58

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T15:25:59.412055Z digest=sha256:1ac8e552fdc7733dd4cd6af94240f2845a498d73c8aa2e9fd0df46fa9f21678a

Observation 5de93053-368f-4076-a270-43c23e2569d3 · inbound

SAMITE: Position Prompted SAM2 with Calibrated Memory for Visual Object Tracking cites this paper.

SAMITE: Position Prompted SAM2 with Calibrated Memory for Visual Object Tracking SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 50

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no resolver link, observed 2026-08-06T12:33:52.639899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:33:52.639899Z digest=sha256:d6046acc597f056eaada8ccd6e7bb4ea535dccc0a1b9aae1572604343c16c030

Observation 7a0af24f-033b-494e-82a2-51bacd051e66 · inbound

FreeVPS: Repurposing Training-Free SAM2 for Generalizable Video Polyp Segmentation cites this paper.

FreeVPS: Repurposing Training-Free SAM2 for Generalizable Video Polyp Segmentation SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 43

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no resolver link, observed 2026-08-05T15:38:04.668203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:38:04.668203Z digest=sha256:c529adfa582a611873e6a0087408bf8bb84f6cda80652d0f55977b0e25c0fbd1

Observation a3f02956-f0d1-4161-862a-3e1a2bff626e · inbound

HERO-VQL: Hierarchical, Egocentric and Robust Visual Query Localization cites this paper.

HERO-VQL: Hierarchical, Egocentric and Robust Visual Query Localization SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 43

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no resolver link, observed 2026-08-05T13:44:11.339769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:44:11.339769Z digest=sha256:90b45e53759e92e7cbc3f34249224af3d121bfd97503cdeab9a9d85e08b644ed

Observation 07863d9e-90b7-4ec3-ab0c-cf0e0ea23b2c · inbound

Zero-Shot Multi-Animal Tracking in the Wild cites this paper.

Zero-Shot Multi-Animal Tracking in the Wild SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 35

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no resolver link, observed 2026-08-04T00:10:00.604587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:10:00.604587Z digest=sha256:f1dc8357e95a814d74d87c131fdb1d76b7a961a31cb01444e483d183ef7742f7

Observation 9e220242-c34f-4058-bf0a-10d6acb5ee61 · inbound

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking cites this paper.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 51

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unresolved
no resolver link, observed 2026-08-03T21:12:07.077803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:12:07.077803Z digest=sha256:34f0103741129ab9d7ff203c83d14ec0a26edbc8ca13cb409436b5449ac57511

Observation 464c6dcc-69bc-4cd2-8360-bdc8f180a9ca · inbound

SAM 3: Segment Anything with Concepts cites this paper.

SAM 3: Segment Anything with Concepts SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 147

Resolution
verified exact
arxiv_id, observed 2026-05-17T20:25:11.484871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-17T20:22:46.220021Z digest=sha256:4f19a8bf9239672f91482de1d908472f39a6558dde027434ea96bb9208162225

Observation 03c05f3b-8e75-4f05-8c6e-16f03ab631e5 · inbound

3AM: 3egment Anything with Geometric Consistency in Videos cites this paper.

3AM: 3egment Anything with Geometric Consistency in Videos SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 98

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T14:21:01.686673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-16T14:19:34.641108Z digest=sha256:33b0388b6cab1ff4047f03d375153e9342386eaade7d5f69927655b5136b36fe

Observation 994fd592-db7c-4d40-b11b-2955d5f4050a · inbound

Mitigating Error Accumulation in Continuous Navigation via Memory-Augmented Kalman Filtering cites this paper.

Mitigating Error Accumulation in Continuous Navigation via Memory-Augmented Kalman Filtering SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-16T09:47:41.860275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-16T09:45:53.868748Z digest=sha256:069b2e8bb343f7a165c22151b746dc280c8e768af451902aa06a0a0cfd0b0d6b

Observation 03ead925-7d59-4c8a-88bf-38fd76f7ed16 · inbound

HVG-3D: Bridging Real and Simulation Domains for 3D-Conditional Hand-Object Interaction Video Synthesis cites this paper.

HVG-3D: Bridging Real and Simulation Domains for 3D-Conditional Hand-Object Interaction Video Synthesis SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-05-14T00:18:30.132648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-14T00:14:36.537688Z digest=sha256:56b0402da13d0c11d02bc84ad326b3f593afe3c39aff652b74ecd05917cf56d2

Observation 1a0b3009-576c-4ccc-a766-5c5937d26588 · inbound

HOIGS: Human-Object Interaction Gaussian Splatting cites this paper.

HOIGS: Human-Object Interaction Gaussian Splatting SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:28:02.542468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-13T17:24:50.043908Z digest=sha256:243eea4378e885ab20d1057e68b7e087e42701bdc1602421e1634f4d1c83b98b

Observation eefd7564-63b1-41f3-83e5-852c1c3cc0ed · inbound

4D Vessel Reconstruction for Benchtop Thrombectomy Analysis cites this paper.

4D Vessel Reconstruction for Benchtop Thrombectomy Analysis SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-10T20:25:46.930402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T18:16:38.725224Z digest=sha256:83cd66e0418131ebf303c6d420c8487665328ecfdab5ccae1ac9bb9e96ec02c1

Observation 6fc81412-d66f-4b21-b63d-41c75667cc03 · inbound

ViewSAM: Learning View-aware Cross-modal Semantics for Weakly Supervised Cross-view Referring Multi-Object Tracking cites this paper.

ViewSAM: Learning View-aware Cross-modal Semantics for Weakly Supervised Cross-view Referring Multi-Object Tracking SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:20:42.565832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-08T18:32:38.644948Z digest=sha256:5f9059e1f49abaccd9b99ae722b7d0da540ff7d3add239780b5d775aa42ef4eb

Observation 4336d58e-4262-4276-987f-9ce5c2f80f3c · inbound

Segment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking cites this paper.

Segment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-22T06:21:10.620576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-22T06:19:30.380438Z digest=sha256:d5dc2534751109bea9a8eb533d3d6a47bd8797bc53802af82903f62b5cf9d8ba

Observation 353dfcfb-7ac6-40f6-b099-daa7a30f641e · inbound

Temporal-Emerged Prompting for Segment Anything in Multiframe Infrared Small Target Detection cites this paper.

Temporal-Emerged Prompting for Segment Anything in Multiframe Infrared Small Target Detection SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 65

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T18:13:49.309179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-29T05:13:51.469018Z digest=sha256:b8e07209e489ac41307d5d674335cf96c3418c1fae9e87fd50048095743f3ad8

Observation e22c3c29-eab2-410f-90d5-cd19a7e1716e · inbound

SUMO: Segment and Track Any Motion with Nonlinear State Space Models cites this paper.

SUMO: Segment and Track Any Motion with Nonlinear State Space Models SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:44:19.468864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T06:37:27.783172Z digest=sha256:0d333bc11ba93506cb0d73ce4d9227b36493310d6df59bf5d281226bc5bedf79

Observation df158df1-66b3-4c15-8e00-63a9bffddb3a · inbound

SAM-MT: Real-Time Interactive Multi-Target Video Segmentation cites this paper.

SAM-MT: Real-Time Interactive Multi-Target Video Segmentation SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-07-10T03:06:43.593613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T03:04:57.109924Z digest=sha256:f29f8aafb2099d96b2505330bfb30bfd599470c2fbfc69e44ee7f430967fcbbd

Observation e7e59353-1601-43bf-a8ba-dfaa5d970eaa · inbound

Efficient Tracking and Understanding Object Transformations cites this paper.

Efficient Tracking and Understanding Object Transformations SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-01T11:55:12.500740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:55:12.500740Z digest=sha256:9e487edbec6880afc0f5c3b4fe333a40d704abdc719223cfdf51289f212cda50

Observation b18d6867-db27-4f40-8d7e-8f3f21b6abdb · inbound

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 cites this paper.

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T11:43:11.608780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:43:11.608780Z digest=sha256:3be770438c0809035a122e28464aebd9af75bcfb110210e76c1fd4ea430148ae

Observation 2445129c-2600-47f4-b86a-16dda6dc79fb · inbound

StreamDAM: Presence-Aware Memory for Real-Time Streaming Video Object Segmentation cites this paper.

StreamDAM: Presence-Aware Memory for Real-Time Streaming Video Object Segmentation SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T14:48:54.119308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:48:54.119308Z digest=sha256:84944147cb1c1e42d4f2f899c303357294b380f61d51bc30e202788b81e3f811