SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost | Paper Citation Record

Observation 11a488a3-9d79-45bd-84bf-3beb1059ecc5 · outbound

This paper cites Xmem++: Production-level video segmenta- tion from few annotated frames.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Xmem++: Production-level video segmenta- tion from few annotated frames

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.738085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 366b346b-2fb1-42a3-9b20-82c3210325bf · outbound

This paper cites One- shot video object segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost One- shot video object segmentation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.726052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 11561c84-e797-4fbf-950d-36de8a62d960 · outbound

This paper cites Rsprompter: Learning to prompt for remote sensing instance segmenta- tion based on visual foundation model.IEEE Transactions on Geoscience and Remote Sensing, 2024.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Rsprompter: Learning to prompt for remote sensing instance segmenta- tion based on visual foundation model.IEEE Transactions on Geoscience and Remote Sensing, 2024

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.714060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ba02cf08-f5f4-4072-95c3-ddd96b478355 · outbound

This paper cites Adaptformer: Adapting vision transformers for scalable visual recognition.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Adaptformer: Adapting vision transformers for scalable visual recognition

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.703563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4a334688-76cb-41b5-8674-3a3d106dde9e · outbound

This paper cites SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:38.439660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db998cdb-5490-40f5-97fe-37adf7115483 · outbound

This paper cites 0.1% data makes segment anything slim.NeurIPS,.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost 0.1% data makes segment anything slim.NeurIPS,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.692814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4c34bce8-2e12-47db-abee-d3958b50182d · outbound

This paper cites Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.682205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4e577a05-e56e-4644-8cdd-8399b2e354d6 · outbound

This paper cites Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.669131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7e4ddc88-dcfd-4521-8ca4-3f5f80beee02 · outbound

This paper cites Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation.NeurIPS, 2021.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation.NeurIPS, 2021

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.656205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f07074bf-67a3-4cd5-8cd0-9247113ec8ae · outbound

This paper cites Tracking anything with de- coupled video segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Tracking anything with de- coupled video segmentation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:38.821648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68e2cdb2-f115-42c5-b0f3-2c108187e7a2 · outbound

This paper cites Putting the object back into video object segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Putting the object back into video object segmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.636635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9b1cc4fd-526c-497a-b21e-a3484ac88c49 · outbound

This paper cites Segment and Track Anything.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment and Track Anything

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:38.984260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a33b334d-66b1-4181-a184-740ff8cbc34e · outbound

This paper cites ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:39.082937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 409ef4a8-5aeb-4347-a106-dceda66c567b · outbound

This paper cites Learning the what and how of annotation in video object segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Learning the what and how of annotation in video object segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.625812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 35c29cac-6a12-481e-84a0-ac4ac2ca8add · outbound

This paper cites Segment anything model 2: an application to 2D and 3D medical images.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything model 2: an application to 2D and 3D medical images

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:39.281260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 642f041d-7bee-48c2-94c4-6b3bac3f550a · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:39.420425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c099b13-52de-4c6f-820c-5c523858aadf · outbound

This paper cites Interactive video object segmentation using global and local transfer modules.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Interactive video object segmentation using global and local transfer modules

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.615372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 58d1537e-41f7-47b0-a316-1aeda0409a70 · outbound

This paper cites A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environment.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environment

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:52:50.520855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d6944856-87ef-495f-a04c-90eb2ac2d4c0 · outbound

This paper cites Prompting visual-language models for efficient video understanding.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Prompting visual-language models for efficient video understanding

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.604426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3c3594b6-e9d5-4f84-86ef-35f0455f93e5 · outbound

This paper cites Segment anything in high qual- ity.NeurIPS, 2023.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything in high qual- ity.NeurIPS, 2023

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.593770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 50853442-a2d1-4ad6-8d6a-4f62cb46ffe0 · outbound

This paper cites Segment any- thing.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment any- thing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.584383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 06580f31-8f5e-41a2-a50f-92f1890d0de8 · outbound

This paper cites Frozen clip models are efficient video learners.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Frozen clip models are efficient video learners

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.574762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3d97282a-0322-42fa-a8d3-8595e413b810 · outbound

This paper cites Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:44.860444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a27319da-c951-430b-95ce-aa2214fc1cdd · outbound

This paper cites Decoupled Weight Decay Regularization.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Decoupled Weight Decay Regularization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:45.975938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46538667-b3ba-4a45-9504-1aea96602a29 · outbound

This paper cites Segment anything in medical images.Nature Communications, 2024.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything in medical images.Nature Communications, 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.562809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 296753c5-d4e9-4a3e-9d0c-e1f19ce65fb1 · outbound

This paper cites Video object segmentation without temporal information.IEEE TPAMI, 2018.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Video object segmentation without temporal information.IEEE TPAMI, 2018

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.545539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 97ffd79f-007d-4c78-84ff-5e994a6b19fc · outbound

This paper cites Segment anything model for medical image analysis: an experimental study.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment anything model for medical image analysis: an experimental study

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.517771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cf47f950-2c8b-4f84-9960-b8b403de068f · outbound

This paper cites Fast video object segmentation by reference- guided mask propagation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Fast video object segmentation by reference- guided mask propagation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.363558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ade024f6-0491-46a6-86ce-d70d8e35fd4f · outbound

This paper cites St-adapter: Parameter-efficient image-to-video transfer learning.NeurIPS, 2022.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost St-adapter: Parameter-efficient image-to-video transfer learning.NeurIPS, 2022

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.187973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fce007a0-bd8a-485a-9603-4ae670e231c8 · outbound

This paper cites Dual- path adaptation from image to video transformers.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Dual- path adaptation from image to video transformers

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:53.020964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c66845a-b417-4fe3-be90-b52433a7d20f · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Pytorch: An imperative style, high-performance deep learning library

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:47.273487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54246d1f-937a-4143-8f44-ca248c0a50a6 · outbound

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

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost The 2017 DAVIS Challenge on Video Object Segmentation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:47.338977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ba348c6-d502-4d91-869a-c166418a4c9c · outbound

This paper cites Disentangling spatial and temporal learning for efficient image-to-video transfer learning.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Disentangling spatial and temporal learning for efficient image-to-video transfer learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:52.962159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4cdc9513-ab3e-4027-a34e-7f0167211ff8 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Learn- ing transferable visual models from natural language super- vision

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:47.507661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54567cfc-c79c-4116-b667-2137cf7a270a · outbound

This paper cites Segment Anything Meets Point Tracking.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Segment Anything Meets Point Tracking

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:47.613125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32d05b03-b271-4e21-ad9f-ba434b00d35e · outbound

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

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost SAM 2: Segment Anything in Images and Videos

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:47.689544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b46505a9-ab4f-4412-a50f-b4457b8763be · outbound

This paper cites Seg- ment anything, from space? InWACV, 2024.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Seg- ment anything, from space? InWACV, 2024

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:52.634283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d2d55a5b-8207-4979-97ea-d2284c541ef0 · outbound

This paper cites Learning fast and robust target models for video object segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Learning fast and robust target models for video object segmentation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:52.441859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6367c98a-127d-4bb1-8f02-dc5c67f8f2ba · outbound

This paper cites Interactive 3D Medical Image Segmentation with SAM 2.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Interactive 3D Medical Image Segmentation with SAM 2

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:48.066282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0af786a1-4ab5-4cc8-94af-fd5a658cad6c · outbound

This paper cites TinySAM: Pushing the Envelope for Efficient Segment Anything Model.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost TinySAM: Pushing the Envelope for Efficient Segment Anything Model

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:48.139202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 145770c0-a7d4-449f-ad6e-75da32188b50 · outbound

This paper cites Towards open-vocabulary video instance segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Towards open-vocabulary video instance segmentation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:52.416992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a28ac603-12cc-45d1-b433-35d72d35297e · outbound

This paper cites F3net: Fu- sion, feedback and focus for salient object detection.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost F3net: Fu- sion, feedback and focus for salient object detection

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:52.133490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8fa47d21-827d-415a-8d7b-019097e79d86 · outbound

This paper cites Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:48.476606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f66ab37f-aead-4a37-b22e-914904281cd9 · outbound

This paper cites Scalable video object segmentation with simplified frame- work.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Scalable video object segmentation with simplified frame- work

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:51.963083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3cf8432a-bead-4b98-9543-340adc1bda27 · outbound

This paper cites Cat-sam: Con- ditional tuning for few-shot adaptation of segment anything model.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Cat-sam: Con- ditional tuning for few-shot adaptation of segment anything model

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:51.886849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2d21e214-7128-4169-94a9-69c759c75ee2 · outbound

This paper cites Sam2-unet: Segment anything 2 makes strong encoder for natural and medical image segmentation.arXiv:2408.08870,.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Sam2-unet: Segment anything 2 makes strong encoder for natural and medical image segmentation.arXiv:2408.08870,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:48.758340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6ec5bef-6694-4bca-b495-7d1b0097f919 · outbound

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

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Efficientsam: Leveraged masked image pretraining for efficient segment anything

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:51.871711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 66dd7019-f941-415a-b79a-1d07b6480998 · outbound

This paper cites Youtube-vos: Sequence-to-sequence video object segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Youtube-vos: Sequence-to-sequence video object segmentation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:51.629829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9ac3aeba-a833-4a41-8e9e-70ccdfed6daa · outbound

This paper cites Track Anything: Segment Anything Meets Videos.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Track Anything: Segment Anything Meets Videos

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:49.056362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 960e79a4-35db-4e07-83ec-aca882a801dc · outbound

This paper cites Efficient video object segmen- tation via network modulation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Efficient video object segmen- tation via network modulation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:51.325468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 71beb037-fafc-43c3-8e60-8a94f15c8c43 · outbound

This paper cites AIM: Adapting image models for efficient video action recognition.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost AIM: Adapting image models for efficient video action recognition

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:51.156717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 907785b0-b6af-41a1-98b3-a28ef3db9675 · outbound

This paper cites Collaborative video object segmentation by foreground-background inte- gration.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Collaborative video object segmentation by foreground-background inte- gration

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:51.066669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5404a6f2-5757-4575-aca4-3a46ccf51623 · outbound

This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:49.455141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b14219f4-0ea2-41f4-8266-4983cc0e55d0 · outbound

This paper cites MobileSAMv2: Faster Segment Anything to Everything.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost MobileSAMv2: Faster Segment Anything to Everything

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:49.547609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ee8bb8f-c9f7-4a37-b36b-eaaa7dc82e06 · outbound

This paper cites Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:49.642417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a027915a-2f96-4f65-8176-e2d4128ae780 · outbound

This paper cites Fast Segment Anything.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Fast Segment Anything

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:49.758396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19b37adb-16b0-4d3f-ad7a-f5ceaa97255e · outbound

This paper cites EdgeSAM: Prompt-In-the-Loop Distillation for SAM.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost EdgeSAM: Prompt-In-the-Loop Distillation for SAM

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:49.890149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6722ea7-d27d-4d4b-a968-83bc9046d004 · outbound

This paper cites Medical SAM 2: Segment medical images as video via Segment Anything Model 2.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:49.909797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e62b112e-18b2-4ce8-8a43-a0b8f4e6efd4 · outbound

This paper cites -” indicates directly combining existing pre-trained models for inference. “Cost.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost -” indicates directly combining existing pre-trained models for inference. “Cost

Reference 61

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T11:52:50.813473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56a8c35a-5af4-4fc7-8199-6c8eecbe5760 · outbound

This paper cites an unresolved cited work.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:52:52.280421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4a59372e-94cc-41ba-9a79-00605792d2b9 · outbound

This paper cites an unresolved cited work.

SAM-I2V: Upgrading SAM to Support Promptable Video Segmentation with Less than 0.2% Training Cost Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:52:52.837961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers