Paper Citation Record · LEDGER

Reasoning Segmentation for Images and Videos: A Survey

As of 8 August 2026, this Paper Citation Record lists 100 of 114 outbound references and 5 inbound Pith citation observations for arXiv:2505.18816.

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

pith.paper-citation-record.v1
2505.18816 v1

Coverage vector

measured 100 of 114 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:27:18.789405Z

measured 105 of 105 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:06:22.967237Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:09:55.361578Z

Reference resolution

100 of 114 outbound references displayed

verified exact2
verified fuzzy32
unresolved66
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2535e581-f34c-49aa-a4cd-90ff023a2e52 · outbound

This paper cites UI-Net: Interactive Artificial Neural Networks for Iterative Image Segmentation Based on a User Model.

Reasoning Segmentation for Images and Videos: A Survey UI-Net: Interactive Artificial Neural Networks for Iterative Image Segmentation Based on a User Model

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:27:20.276725Z

Source-reported events for the cited work

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Observation 5104d3b1-8a63-48c0-bd05-b019af82bf66 · outbound

This paper cites ViCaS: A Dataset for Combining Holistic and Pixel-level Video Understanding using Captions with Grounded Segmentation.

Reasoning Segmentation for Images and Videos: A Survey ViCaS: A Dataset for Combining Holistic and Pixel-level Video Understanding using Captions with Grounded Segmentation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.072412Z

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Observation 5628c86b-4642-451e-80ca-aa9b60782db4 · outbound

This paper cites Burst: A benchmark for unifying object recognition, 39 segmentation and tracking in video, in: Proceedings of the IEEE/CVF winter conference on applications of computer vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Burst: A benchmark for unifying object recognition, 39 segmentation and tracking in video, in: Proceedings of the IEEE/CVF winter conference on applications of computer vision, pp

Reference 3

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Observation 1596bf16-837f-4dc4-bc2f-653d81fd4952 · outbound

This paper cites One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos.

Reasoning Segmentation for Images and Videos: A Survey One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos

Reference 4

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Observation 98bc1725-92aa-476a-a66b-6da70b393a0b · outbound

This paper cites Cores: Orchestrating the dance of reasoning and segmentation, in: European Conference on Computer Vision, Springer.

Reasoning Segmentation for Images and Videos: A Survey Cores: Orchestrating the dance of reasoning and segmentation, in: European Conference on Computer Vision, Springer

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.273826Z

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Observation f2799ce2-0ec9-4498-aadb-2f0dd8d18212 · outbound

This paper cites Xmem++: Production-level video segmentation from few annotated frames, in: Pro- ceedings of the IEEE/CVF International Conference on Computer Vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Xmem++: Production-level video segmentation from few annotated frames, in: Pro- ceedings of the IEEE/CVF International Conference on Computer Vision, pp

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.329047Z

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Observation 3e7199cf-1e6b-407e-b00d-f1c96ac9424c · outbound

This paper cites Coco-stuff: Thing and stuff classes in context, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Coco-stuff: Thing and stuff classes in context, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp

Reference 7

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Observation 54b9c109-2a0d-4591-b8e9-1cb2d4b7aada · outbound

This paper cites Coco-stuff: Thing and stuff classes in context, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Coco-stuff: Thing and stuff classes in context, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.489319Z

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Observation f732ecc8-2281-48dc-9fa4-6ee936b81096 · outbound

This paper cites Pixel-Level Reasoning Segmentation via Multi-turn Conversations.

Reasoning Segmentation for Images and Videos: A Survey Pixel-Level Reasoning Segmentation via Multi-turn Conversations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.587733Z

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Observation a2672107-2874-4dd1-9b28-4eb09fc36747 · outbound

This paper cites End-to-end object detection with transformers, in: European conference on computer vision, Springer.

Reasoning Segmentation for Images and Videos: A Survey End-to-end object detection with transformers, in: European conference on computer vision, Springer

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.653276Z

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Observation 9c17b8da-d672-4c2d-8dcf-003f75f2aa62 · outbound

This paper cites an unresolved cited work.

Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 11

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Observation 0cf067c6-6e1d-49e2-b69c-d469484d8642 · outbound

This paper cites an unresolved cited work.

Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.868491Z

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Observation 0023a925-9097-4578-b971-51f60d688532 · outbound

This paper cites Sam4mllm: Enhance multi-modal large language model for referring ex- pression segmentation, in: European Conference on Computer Vision, Springer.

Reasoning Segmentation for Images and Videos: A Survey Sam4mllm: Enhance multi-modal large language model for referring ex- pression segmentation, in: European Conference on Computer Vision, Springer

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.942872Z

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Observation 4250dca0-38ea-4da1-bb92-80a94ba49762 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Masked-attention mask transformer for universal image segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:11.987613Z

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Observation 1ed77509-9ee5-4d18-adb0-fd733b49b0dc · outbound

This paper cites Xmem: Long-term video object seg- mentation with an atkinson-shiffrin memory model, in: European Confer- ence on Computer Vision, Springer.

Reasoning Segmentation for Images and Videos: A Survey Xmem: Long-term video object seg- mentation with an atkinson-shiffrin memory model, in: European Confer- ence on Computer Vision, Springer

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:12.062712Z

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Observation 47fd545a-b396-4222-bb23-690101e7ba9a · outbound

This paper cites Vocabulary-free image classification.

Reasoning Segmentation for Images and Videos: A Survey Vocabulary-free image classification

Reference 16

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Observation cf1d2c9b-d29f-4510-bfab-118019625441 · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Scannet: Richly-annotated 3d reconstructions of indoor scenes, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:12.225657Z

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Observation e90944a5-7290-4d20-87f3-5469fca853cc · outbound

This paper cites Tao: A large-scale benchmark for tracking any object, in: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part V 16, Springer.

Reasoning Segmentation for Images and Videos: A Survey Tao: A large-scale benchmark for tracking any object, in: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part V 16, Springer

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:12.305165Z

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Observation 82302091-de9e-46e9-bae2-48fc6dbb0626 · outbound

This paper cites Motion-Grounded Video Reasoning: Understanding and Perceiving Motion at Pixel Level.

Reasoning Segmentation for Images and Videos: A Survey Motion-Grounded Video Reasoning: Understanding and Perceiving Motion at Pixel Level

Reference 19

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Observation a4b13401-579b-4aad-ac1a-9744ffa96064 · outbound

This paper cites Mevis: A large-scale benchmark for video segmentation with motion expressions, in: Proceed- ings of the IEEE/CVF International Conference on Computer Vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Mevis: A large-scale benchmark for video segmentation with motion expressions, in: Proceed- ings of the IEEE/CVF International Conference on Computer Vision, pp

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:12.500258Z

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Observation 783e111d-b744-4e99-b275-4ac4768809cb · outbound

This paper cites Mose: A new dataset for video object segmentation in complex scenes, in: Pro- ceedings of the IEEE/CVF international conference on computer vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Mose: A new dataset for video object segmentation in complex scenes, in: Pro- ceedings of the IEEE/CVF international conference on computer vision, pp

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:12.592565Z

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Observation 579de55c-4d1f-4f10-b152-c97f38c742c9 · outbound

This paper cites Panoptic Segmentation: A Review.

Reasoning Segmentation for Images and Videos: A Survey Panoptic Segmentation: A Review

Reference 22

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Observation bcf025c8-490b-4b28-b496-4f577043241f · outbound

This paper cites Oops! predicting unintentional action in video, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Oops! predicting unintentional action in video, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:12.718042Z

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Observation 56a0ce34-9da4-4754-8128-2335acf07537 · outbound

This paper cites A Survey for Foundation Models in Autonomous Driving.

Reasoning Segmentation for Images and Videos: A Survey A Survey for Foundation Models in Autonomous Driving

Reference 24

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Observation abe7de4f-a2cf-4111-ac9e-f8fe5fd37ed8 · outbound

This paper cites Part- aware panoptic segmentation, in: Proceedings of the IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Part- aware panoptic segmentation, in: Proceedings of the IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition, pp

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:12.927968Z

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Observation 770e0673-4881-4b20-abde-e9f044696652 · outbound

This paper cites The Devil is in Temporal Token: High Quality Video Reasoning Segmentation.

Reasoning Segmentation for Images and Videos: A Survey The Devil is in Temporal Token: High Quality Video Reasoning Segmentation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:13.039735Z

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Observation d3443753-da5e-48db-b968-d39eaebd1a60 · outbound

This paper cites The iapr tc-12 benchmark: A new evaluation resource for visual information systems, in: International workshop ontoImage, pp.

Reasoning Segmentation for Images and Videos: A Survey The iapr tc-12 benchmark: A new evaluation resource for visual information systems, in: International workshop ontoImage, pp

Reference 27

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Observation b0496995-8774-403f-a4dd-cde1f9e7a271 · outbound

This paper cites Lvis: A dataset for large vocabu- lary instance segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Lvis: A dataset for large vocabu- lary instance segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 28

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Observation 3b31db6e-4004-49a0-9ed4-73dddcf0523d · outbound

This paper cites A survey on instance segmentation: state of the art.

Reasoning Segmentation for Images and Videos: A Survey A survey on instance segmentation: state of the art

Reference 29

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Observation 99f2b6af-40a8-4263-8878-38917cb669dd · outbound

This paper cites A brief survey on semantic segmentation with deep learning.

Reasoning Segmentation for Images and Videos: A Survey A brief survey on semantic segmentation with deep learning

Reference 30

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Observation c2a94a13-f9d0-4335-aa48-30e7e1af3941 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Reasoning Segmentation for Images and Videos: A Survey LoRA: Low-Rank Adaptation of Large Language Models

Reference 31

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Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 32

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Observation d3d0aa40-7f13-4279-b0aa-637e14b53d26 · outbound

This paper cites MMR: A Large-scale Benchmark Dataset for Multi-target and Multi-granularity Reasoning Segmentation.

Reasoning Segmentation for Images and Videos: A Survey MMR: A Large-scale Benchmark Dataset for Multi-target and Multi-granularity Reasoning Segmentation

Reference 33

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This paper cites Referitgame: Referring to objects in photographs of natural scenes, in: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), pp.

Reasoning Segmentation for Images and Videos: A Survey Referitgame: Referring to objects in photographs of natural scenes, in: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), pp

Reference 34

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Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 35

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Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 36

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This paper cites Segment Anything.

Reasoning Segmentation for Images and Videos: A Survey Segment Anything

Reference 37

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Observation 35d9f209-ff49-4b67-aded-df2dbded454b · outbound

This paper cites Visual genome: Connecting language and vision using crowdsourced dense image annota- tions.

Reasoning Segmentation for Images and Videos: A Survey Visual genome: Connecting language and vision using crowdsourced dense image annota- tions

Reference 38

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This paper cites The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale.

Reasoning Segmentation for Images and Videos: A Survey The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale

Reference 39

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This paper cites Lisa: Reasoning segmentation via large language model, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Lisa: Reasoning segmentation via large language model, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 40

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This paper cites Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language mod- els, in: International conference on machine learning, PMLR.

Reasoning Segmentation for Images and Videos: A Survey Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language mod- els, in: International conference on machine learning, PMLR

Reference 41

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This paper cites SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model.

Reasoning Segmentation for Images and Videos: A Survey SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model

Reference 42

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This paper cites Robust referring video object segmentation with cyclic structural consensus, in: Proceed- ings of the IEEE/CVF International Conference on Computer Vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Robust referring video object segmentation with cyclic structural consensus, in: Proceed- ings of the IEEE/CVF International Conference on Computer Vision, pp

Reference 43

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This paper cites Llama-vid: An image is worth 2 tokens in large language models, in: European Conference on Computer Vision, Springer.

Reasoning Segmentation for Images and Videos: A Survey Llama-vid: An image is worth 2 tokens in large language models, in: European Conference on Computer Vision, Springer

Reference 44

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This paper cites Microsoft coco: Common objects in context, in: Computer Vision–ECCV 2014: 13th European Confer- ence, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13, Springer.

Reasoning Segmentation for Images and Videos: A Survey Microsoft coco: Common objects in context, in: Computer Vision–ECCV 2014: 13th European Confer- ence, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13, Springer

Reference 45

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This paper cites Gres: Generalized referring expression segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Gres: Generalized referring expression segmentation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 46

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Reasoning Segmentation for Images and Videos: A Survey Visual instruction tuning

Reference 47

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This paper cites Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement.

Reasoning Segmentation for Images and Videos: A Survey Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement

Reference 48

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This paper cites Ground abstract structure concepts of scaffolding systems for automatic compliance check- ing based on reasoning segmentation.

Reasoning Segmentation for Images and Videos: A Survey Ground abstract structure concepts of scaffolding systems for automatic compliance check- ing based on reasoning segmentation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.635044Z

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This paper cites Video anomaly detection and explanation via large language models.

Reasoning Segmentation for Images and Videos: A Survey Video anomaly detection and explanation via large language models

Reference 50

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Observation dc0c66bc-dbca-49f9-9a4f-6239e505fd84 · outbound

This paper cites Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models.

Reasoning Segmentation for Images and Videos: A Survey Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 51

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Observation 41bdf037-fc82-43e5-b1cd-8f4d9b98bd02 · outbound

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Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 52

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Source-reported events for the cited work

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Observation 4552696c-2c40-4fcf-8ca9-645ee71e25db · outbound

This paper cites Large-scale video panoptic segmentation in the wild: A benchmark, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pat- tern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Large-scale video panoptic segmentation in the wild: A benchmark, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pat- tern Recognition, pp

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.603088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d7785866-13af-4b67-a815-1f83c89251f6 · outbound

This paper cites Image segmentation using deep learning: A survey.

Reasoning Segmentation for Images and Videos: A Survey Image segmentation using deep learning: A survey

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.594634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e0d0e917-465d-46e7-9e8d-6def35c33a95 · outbound

This paper cites GPT-4 Technical Report.

Reasoning Segmentation for Images and Videos: A Survey GPT-4 Technical Report

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.586466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1d4d6a45-bf66-432c-8b22-6c4f1b2ab48f · outbound

This paper cites GPT-4V(ision) System Card.

Reasoning Segmentation for Images and Videos: A Survey GPT-4V(ision) System Card

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.578848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 53191d63-744b-4e11-9acd-8cc39efae377 · outbound

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

Reasoning Segmentation for Images and Videos: A Survey DINOv2: Learning Robust Visual Features without Supervision

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:16.276213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e9a4395-0340-4ad8-92db-1bdbc82aa975 · outbound

This paper cites Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models, in: Proceedings of the IEEE international conference on computer vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models, in: Proceedings of the IEEE international conference on computer vision, pp

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.570111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 264110e8-d488-4fd7-ba05-e7207fa041de · outbound

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

Reasoning Segmentation for Images and Videos: A Survey The 2017 DAVIS Challenge on Video Object Segmentation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:16.379401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 184032c2-86a5-4be1-8391-b84572ca2e99 · outbound

This paper cites Occluded video instance segmentation: A benchmark.

Reasoning Segmentation for Images and Videos: A Survey Occluded video instance segmentation: A benchmark

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.560685Z

Source-reported events for the cited work

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Observation 316d3aa7-825b-4253-8944-3f4469407fdb · outbound

This paper cites Reasoning to attend: Try to understand how< seg> token works.

Reasoning Segmentation for Images and Videos: A Survey Reasoning to attend: Try to understand how< seg> token works

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:16.459345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a67f527-dab8-4bf5-bee0-62f351497b25 · outbound

This paper cites Learning trans- ferable visual models from natural language supervision, in: International conference on machine learning, PMLR.

Reasoning Segmentation for Images and Videos: A Survey Learning trans- ferable visual models from natural language supervision, in: International conference on machine learning, PMLR

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.552768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e994d17d-0097-423f-9f4c-bbda7b8edf20 · outbound

This paper cites Paco: Parts and attributes of common objects, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Paco: Parts and attributes of common objects, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.544550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f5f67165-0da6-4ff5-9b25-611289af9cd7 · outbound

This paper cites Glamm: Pixelground- inglargemultimodalmodel, in: ProceedingsoftheIEEE/CVFConference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Glamm: Pixelground- inglargemultimodalmodel, in: ProceedingsoftheIEEE/CVFConference on Computer Vision and Pattern Recognition, pp

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.536167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d5e00767-6e8e-4f2e-bc96-94c6afd01c47 · outbound

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

Reasoning Segmentation for Images and Videos: A Survey SAM 2: Segment Anything in Images and Videos

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:16.663543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13e78c09-8f72-4f36-a0a7-99b403efb154 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Reasoning Segmentation for Images and Videos: A Survey Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:16.717849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 018d04b0-a9d8-4d8e-9aa5-5213379dccff · outbound

This paper cites Pixellm: Pixel reasoning with large multimodal model, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Pixellm: Pixel reasoning with large multimodal model, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.527449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b7865683-1aa7-4cf3-8385-19d6aa57d54a · outbound

This paper cites Object Hallucination in Image Captioning.

Reasoning Segmentation for Images and Videos: A Survey Object Hallucination in Image Captioning

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:16.801705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f488d60a-fcf2-408d-908e-3ea4f8cb5ed5 · outbound

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Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 69

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:27:20.518963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8f6a796f-b9c3-43eb-afa1-2f3b46f58aae · outbound

This paper cites Position: Foundation Models Need Digital Twin Representations.

Reasoning Segmentation for Images and Videos: A Survey Position: Foundation Models Need Digital Twin Representations

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:16.888010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6154626e-f598-42ac-b4cf-248e91f05f2b · outbound

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Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:27:20.510072Z

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Observation ab7aff1f-a7d5-44b9-82d4-6c5c1e4bc53a · outbound

This paper cites RVTBench: A Benchmark for Visual Reasoning Tasks.

Reasoning Segmentation for Images and Videos: A Survey RVTBench: A Benchmark for Visual Reasoning Tasks

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:16.976460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6260a082-1e7a-49cf-8066-b91dd9288ce4 · outbound

This paper cites Operating Room Workflow Analysis via Reasoning Segmentation over Digital Twins.

Reasoning Segmentation for Images and Videos: A Survey Operating Room Workflow Analysis via Reasoning Segmentation over Digital Twins

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.030764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92574bd9-3902-4306-b588-39bf8b41ed14 · outbound

This paper cites Online Reasoning Video Segmentation with Just-in-Time Digital Twins.

Reasoning Segmentation for Images and Videos: A Survey Online Reasoning Video Segmentation with Just-in-Time Digital Twins

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.086609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d201cc74-11a5-4ff9-b09c-545f0a9bf9ca · outbound

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Reasoning Segmentation for Images and Videos: A Survey Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:27:20.501488Z

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Observation e75943ca-b73f-4740-b246-86923e47b367 · outbound

This paper cites EVA-CLIP: Improved Training Techniques for CLIP at Scale.

Reasoning Segmentation for Images and Videos: A Survey EVA-CLIP: Improved Training Techniques for CLIP at Scale

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.198173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed7bddb8-2d12-4292-9d58-85e2c9f5c624 · outbound

This paper cites Growcut: Interactive multi-label nd image segmentation by cellular automata, in: proc.

Reasoning Segmentation for Images and Videos: A Survey Growcut: Interactive multi-label nd image segmentation by cellular automata, in: proc

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.493778Z

Source-reported events for the cited work

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Observation 02c0e07d-8a62-4754-b277-3d52456ef1a1 · outbound

This paper cites Reducing the annotation effort for video object segmentation datasets, in: Proceed- ings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Reducing the annotation effort for video object segmentation datasets, in: Proceed- ings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.484452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7b617589-b580-4d20-a999-c99295fe8c3a · outbound

This paper cites Prima: Multi-image vision-language models for reasoning segmentation.

Reasoning Segmentation for Images and Videos: A Survey Prima: Multi-image vision-language models for reasoning segmentation

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.319384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5194841-dd28-44a5-bad6-18c571d4eda9 · outbound

This paper cites Ov-vis: Open-vocabulary video instance segmentation.

Reasoning Segmentation for Images and Videos: A Survey Ov-vis: Open-vocabulary video instance segmentation

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.475048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4f1441ef-eeb7-4181-9c0a-80a193c00a37 · outbound

This paper cites Towards open-vocabulary video instance segmentation, in: proceedings of the IEEE/CVF international conference on computer vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Towards open-vocabulary video instance segmentation, in: proceedings of the IEEE/CVF international conference on computer vision, pp

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.465799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 77313945-d7f1-4d7f-8ddb-150254cd2b55 · outbound

This paper cites Llm-seg: Bridging image segmentation and large language model reasoning, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Llm-seg: Bridging image segmentation and large language model reasoning, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.457907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 135e0f7e-ac33-4b4b-822b-7803a27d02ac · outbound

This paper cites Unidentified video objects: A benchmark for dense, open-world segmentation, in: Proceed- ings of the IEEE/CVF international conference on computer vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Unidentified video objects: A benchmark for dense, open-world segmentation, in: Proceed- ings of the IEEE/CVF international conference on computer vision, pp

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.450167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 69049e09-7e92-4305-a151-604abd22817f · outbound

This paper cites SegLLM: Multi-round Reasoning Segmentation.

Reasoning Segmentation for Images and Videos: A Survey SegLLM: Multi-round Reasoning Segmentation

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.599286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c58eabf6-7f01-4e6e-92c4-d9cbc0d0ad04 · outbound

This paper cites LaSagnA: Language-based Segmentation Assistant for Complex Queries.

Reasoning Segmentation for Images and Videos: A Survey LaSagnA: Language-based Segmentation Assistant for Complex Queries

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.662473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84d1e245-ea60-4124-8039-1caec776250d · outbound

This paper cites InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language Models.

Reasoning Segmentation for Images and Videos: A Survey InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language Models

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.717014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87f917ea-32ca-4d10-a3e9-72157c73ce39 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Reasoning Segmentation for Images and Videos: A Survey Chain-of-thought prompting elicits reasoning in large language models

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.757478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4eeaab8-288b-41c1-a4a6-1bde2a30ff2b · outbound

This paper cites Ov- parts: Towards open-vocabulary part segmentation.

Reasoning Segmentation for Images and Videos: A Survey Ov- parts: Towards open-vocabulary part segmentation

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.437125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d94a26f9-d9b2-495b-a66b-3aec75517bdd · outbound

This paper cites Phrasecut: Language- based image segmentation in the wild, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Phrasecut: Language- based image segmentation in the wild, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.428859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 482a4945-58ae-4189-81d3-31cdb93c7b47 · outbound

This paper cites See say and segment: Teaching lmms to overcome false premises, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey See say and segment: Teaching lmms to overcome false premises, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.420604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1682cf05-b69a-4cd6-a225-5c8f435a83c4 · outbound

This paper cites Gsva: Generalized segmentation via multimodal large language models, in: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Gsva: Generalized segmentation via multimodal large language models, in: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.411628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2aeeff76-74e6-4d7e-a14a-eace992817c2 · outbound

This paper cites Youtube-vos: Sequence-to-sequence video object segmentation, in: Proceedings of the European conference on computer vision (ECCV), pp.

Reasoning Segmentation for Images and Videos: A Survey Youtube-vos: Sequence-to-sequence video object segmentation, in: Proceedings of the European conference on computer vision (ECCV), pp

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.402971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a8374649-c868-43fb-a8d0-65a273149fd8 · outbound

This paper cites Visa: Reasoning video object segmentation via large language models, in: European Conference on Computer Vision, Springer.

Reasoning Segmentation for Images and Videos: A Survey Visa: Reasoning video object segmentation via large language models, in: European Conference on Computer Vision, Springer

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.395243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a40796a9-b8ff-4ef7-8d6d-11208ac46186 · outbound

This paper cites Panop- tic scene graph generation, in: European Conference on Computer Vision, Springer.

Reasoning Segmentation for Images and Videos: A Survey Panop- tic scene graph generation, in: European Conference on Computer Vision, Springer

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.386965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0f8c2825-a571-46e7-ab1b-7d7dde838826 · outbound

This paper cites Video instance segmentation, in: Pro- ceedings of the IEEE/CVF international conference on computer vision, pp.

Reasoning Segmentation for Images and Videos: A Survey Video instance segmentation, in: Pro- ceedings of the IEEE/CVF international conference on computer vision, pp

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.379641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5eadc24a-072c-40ed-a1b0-bfaa947003b7 · outbound

This paper cites Depth Anything V2.

Reasoning Segmentation for Images and Videos: A Survey Depth Anything V2

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:18.497202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d846f45-b74d-4917-bef0-fe69edc5c59d · outbound

This paper cites An improved baseline for reasoning segmentation with large language model.

Reasoning Segmentation for Images and Videos: A Survey An improved baseline for reasoning segmentation with large language model

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.369615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 61a7ef6b-27f3-4b50-8a02-cc88f72dbcf5 · outbound

This paper cites Empowering Segmentation Ability to Multi-modal Large Language Models.

Reasoning Segmentation for Images and Videos: A Survey Empowering Segmentation Ability to Multi-modal Large Language Models

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:18.655378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation add5e5f7-086d-41d7-be11-5af856289345 · outbound

This paper cites Follow the rules: reasoning for video anomaly detection with large language models, in: European Conference on Computer Vision, Springer.

Reasoning Segmentation for Images and Videos: A Survey Follow the rules: reasoning for video anomaly detection with large language models, in: European Conference on Computer Vision, Springer

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.360394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a8ad9b85-c90d-4b59-b68f-c088e2d7806d · outbound

This paper cites Lavt: Language-aware vision transformer for referring image segmenta- tion, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

Reasoning Segmentation for Images and Videos: A Survey Lavt: Language-aware vision transformer for referring image segmenta- tion, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.350859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation 6507a37d-5882-44da-844d-3acb78c39a8e · inbound

Temporally-Constrained Video Reasoning Segmentation and Automated Benchmark Construction cites this paper.

Temporally-Constrained Video Reasoning Segmentation and Automated Benchmark Construction Reasoning Segmentation for Images and Videos: A Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:06:22.967237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dba12a3-d13f-4f62-8e1e-4ff91d86e7a5 · inbound

GTPBD-MM: A Global Terraced Parcel and Boundary Dataset with Multi-Modality cites this paper.

GTPBD-MM: A Global Terraced Parcel and Boundary Dataset with Multi-Modality Reasoning Segmentation for Images and Videos: A Survey

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:41:00.225117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 99dbdaa5-f54f-43cb-989b-8cf35a603dd1 · inbound

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation cites this paper.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Reasoning Segmentation for Images and Videos: A Survey

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:46:14.156308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation faaf51be-153a-4a61-9ba3-1c7b12e6a4a4 · inbound

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models Reasoning Segmentation for Images and Videos: A Survey

Reference 12

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DGSeg: Dynamic Gating of Semantic-Spatial Guided Predictions for Reasoning Segmentation cites this paper.

DGSeg: Dynamic Gating of Semantic-Spatial Guided Predictions for Reasoning Segmentation Reasoning Segmentation for Images and Videos: A Survey

Reference 44

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