Transforming Static Images Using Generative Models for Video Salient Object Detection | Paper Citation Record

Observation a244aabf-9a9b-4f47-b783-27c0da3e8613 · outbound

This paper cites Frequency-tuned salient region de- tection.

Transforming Static Images Using Generative Models for Video Salient Object Detection Frequency-tuned salient region de- tection

Reference 1

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Observation b0da04a9-edf6-4339-9ba1-2744b246623b · outbound

This paper cites Stem-seg: Spatio-temporal em- beddings for instance segmentation in videos.

Transforming Static Images Using Generative Models for Video Salient Object Detection Stem-seg: Spatio-temporal em- beddings for instance segmentation in videos

Reference 2

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Observation b3017906-ab9c-4d57-87a3-9f90f9b6e2e1 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Transforming Static Images Using Generative Models for Video Salient Object Detection Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 3

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Observation fe857f3b-b63f-44c8-b6a5-dff480e3898e · outbound

This paper cites A thin-plate spline and the decomposition of deformations.

Transforming Static Images Using Generative Models for Video Salient Object Detection A thin-plate spline and the decomposition of deformations

Reference 4

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Observation 5fc33399-4691-489d-b9a2-baa64f46ecb3 · outbound

This paper cites Video generation models as world simulators.

Transforming Static Images Using Generative Models for Video Salient Object Detection Video generation models as world simulators

Reference 5

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Observation 4f25e8ea-10c1-4ca2-9fec-f575aedf37fb · outbound

This paper cites Video salient object detection via contrastive features and attention modules.

Transforming Static Images Using Generative Models for Video Salient Object Detection Video salient object detection via contrastive features and attention modules

Reference 6

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Observation 40b29569-0028-47ae-8534-dd3de67bdc3c · outbound

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

Transforming Static Images Using Generative Models for Video Salient Object Detection Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model

Reference 7

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Observation 336dae8f-3bd5-4546-ae8c-5ce038108b17 · outbound

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

Transforming Static Images Using Generative Models for Video Salient Object Detection Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation

Reference 8

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Observation f29e952b-07c5-42e9-b33a-9148152715da · outbound

This paper cites Global contrast based salient region detection.

Transforming Static Images Using Generative Models for Video Salient Object Detection Global contrast based salient region detection

Reference 9

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Observation 8b885a3f-80a6-4b49-b099-9d791aae4a92 · outbound

This paper cites Tack- ling background distraction in video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Tack- ling background distraction in video object segmentation

Reference 10

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Observation a932a8b6-1014-42cd-af8c-7affbe01e5a6 · outbound

This paper cites Treating mo- tion as option to reduce motion dependency in unsupervised video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Treating mo- tion as option to reduce motion dependency in unsupervised video object segmentation

Reference 11

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Observation d5800a6f-9a34-46bc-8fc4-76cb8f702f18 · outbound

This paper cites Dual pro- totype attention for unsupervised video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Dual pro- totype attention for unsupervised video object segmentation

Reference 12

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Observation 3e783403-4183-433b-8412-b594e6a24d0f · outbound

This paper cites 3d u-net: learn- ing dense volumetric segmentation from sparse annota- tion.

Transforming Static Images Using Generative Models for Video Salient Object Detection 3d u-net: learn- ing dense volumetric segmentation from sparse annota- tion

Reference 13

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Observation c572fe00-5bb2-495b-92ba-d0cf9a05c2c2 · outbound

This paper cites The pascal visual object classes (voc) challenge.

Transforming Static Images Using Generative Models for Video Salient Object Detection The pascal visual object classes (voc) challenge

Reference 14

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Observation 3d6339c5-ef8a-42cb-ab16-38e28ec13060 · outbound

This paper cites Structure-measure: A new way to evaluate foreground maps.

Transforming Static Images Using Generative Models for Video Salient Object Detection Structure-measure: A new way to evaluate foreground maps

Reference 15

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Observation 5663bf56-78eb-400e-8407-efd87eb69842 · outbound

This paper cites Shifting more attention to video salient object detection.

Transforming Static Images Using Generative Models for Video Salient Object Detection Shifting more attention to video salient object detection

Reference 16

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Observation 274a7dfe-9396-4b33-b125-6a8150cbc02c · outbound

This paper cites Bidirectionally learning dense spatio-temporal feature prop- agation network for unsupervised video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Bidirectionally learning dense spatio-temporal feature prop- agation network for unsupervised video object segmentation

Reference 17

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Observation bb95c596-3757-4674-b5e2-ff6c6d419f57 · outbound

This paper cites Temporally efficient gabor transformer for unsu- pervised video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Temporally efficient gabor transformer for unsu- pervised video object segmentation

Reference 18

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Observation 0c4e0e0c-22d9-4b70-9067-722e2668de4c · outbound

This paper cites Pyramid constrained self- attention network for fast video salient object detection.

Transforming Static Images Using Generative Models for Video Salient Object Detection Pyramid constrained self- attention network for fast video salient object detection

Reference 19

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Observation 7b6215f5-3a99-4e22-95e4-0faac167852f · outbound

This paper cites Sparsectrl: Adding sparse controls to text-to-video diffusion models.

Transforming Static Images Using Generative Models for Video Salient Object Detection Sparsectrl: Adding sparse controls to text-to-video diffusion models

Reference 20

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Observation 45352cf1-ca2c-4c09-92c3-3264450d58db · outbound

This paper cites Semantic contours from inverse detectors.

Transforming Static Images Using Generative Models for Video Salient Object Detection Semantic contours from inverse detectors

Reference 21

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Observation b2f82f1e-dc0d-437c-8787-15a1dc13b57b · outbound

This paper cites Classifier-Free Diffusion Guidance.

Transforming Static Images Using Generative Models for Video Salient Object Detection Classifier-Free Diffusion Guidance

Reference 22

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Observation 24c001fc-11c1-434c-b179-dbed73c44bdb · outbound

This paper cites Denoising dif- fusion probabilistic models.

Transforming Static Images Using Generative Models for Video Salient Object Detection Denoising dif- fusion probabilistic models

Reference 23

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Observation 25bcfe3f-b97a-4d32-8a93-14f27b9d0ed5 · outbound

This paper cites Full-duplex strategy for video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Full-duplex strategy for video object segmentation

Reference 24

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Observation 37b38d93-7160-45de-955b-b8e634b9810c · outbound

This paper cites Casnet: A cross-attention siamese net- work for video salient object detection.

Transforming Static Images Using Generative Models for Video Salient Object Detection Casnet: A cross-attention siamese net- work for video salient object detection

Reference 25

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Observation 689577ec-3821-44a1-997e-69c91a99d234 · outbound

This paper cites Auto-Encoding Variational Bayes.

Transforming Static Images Using Generative Models for Video Salient Object Detection Auto-Encoding Variational Bayes

Reference 26

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Observation 30412447-1bbf-44d4-bdfd-07f97dde6158 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Transforming Static Images Using Generative Models for Video Salient Object Detection Adam: A Method for Stochastic Optimization

Reference 27

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Observation a7bd2834-1080-4b3c-9c53-e6e4b4dd9a1f · outbound

This paper cites Pika 1.0, 2023.

Transforming Static Images Using Generative Models for Video Salient Object Detection Pika 1.0, 2023

Reference 28

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Observation 174144dd-921b-403e-bf75-31306c102a49 · outbound

This paper cites Unsupervised video object seg- mentation via prototype memory network.

Transforming Static Images Using Generative Models for Video Salient Object Detection Unsupervised video object seg- mentation via prototype memory network

Reference 29

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Observation 598f9126-f370-40c1-94cf-1f73e70ffae4 · outbound

This paper cites Guided slot attention for unsupervised video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Guided slot attention for unsupervised video object segmentation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:44:08.877986Z

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Observation ae2c48c5-7947-4b7f-a7b2-1aeaf640a1aa · outbound

This paper cites Mo- tion guided attention for video salient object detection.

Transforming Static Images Using Generative Models for Video Salient Object Detection Mo- tion guided attention for video salient object detection

Reference 31

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Observation 17d40b90-c8bd-4305-8c6a-ac448ae7b20b · outbound

This paper cites Movideo: Motion-aware video generation with diffusion model.

Transforming Static Images Using Generative Models for Video Salient Object Detection Movideo: Motion-aware video generation with diffusion model

Reference 32

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Observation a395b513-7195-42c5-a617-b41f10002e5b · outbound

This paper cites Making a Case for 3D Convolutions for Object Segmentation in Videos.

Transforming Static Images Using Generative Models for Video Salient Object Detection Making a Case for 3D Convolutions for Object Segmentation in Videos

Reference 33

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Observation 57e33847-88cc-4ade-a4c5-09ed2de78ba3 · outbound

This paper cites Segmentation of moving objects by long term video analysis.

Transforming Static Images Using Generative Models for Video Salient Object Detection Segmentation of moving objects by long term video analysis

Reference 34

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Observation 63e901eb-f817-4dfb-8b82-8937d5744fc7 · outbound

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

Transforming Static Images Using Generative Models for Video Salient Object Detection Fast video object segmentation by reference- guided mask propagation

Reference 35

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Observation 570463cf-fe93-48fb-9f56-ae096e8a5526 · outbound

This paper cites Video object segmentation using space-time memory networks.

Transforming Static Images Using Generative Models for Video Salient Object Detection Video object segmentation using space-time memory networks

Reference 36

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Observation 8ab48d67-0e22-4b7f-9905-b7cbda1bbebc · outbound

This paper cites Multi-scale interactive network for salient object detection.

Transforming Static Images Using Generative Models for Video Salient Object Detection Multi-scale interactive network for salient object detection

Reference 37

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Observation 190fa514-586e-4de8-bf12-24641e6a1c1f · outbound

This paper cites Hierarchical feature align- ment network for unsupervised video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Hierarchical feature align- ment network for unsupervised video object segmentation

Reference 38

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Observation f4756ff3-8954-40f1-ae49-41273e9c5b86 · outbound

This paper cites A benchmark dataset and evaluation methodology for video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection A benchmark dataset and evaluation methodology for video object segmentation

Reference 39

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Observation 5b9e1345-bb1c-4d7c-83a1-9e41bc4a6e8a · outbound

This paper cites Learning video object segmentation from static images.

Transforming Static Images Using Generative Models for Video Salient Object Detection Learning video object segmentation from static images

Reference 40

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Observation aa0ac10c-112c-46af-bd0f-e1ab43b3d795 · outbound

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

Transforming Static Images Using Generative Models for Video Salient Object Detection High-resolution image synthesis with latent diffusion models

Reference 41

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Observation bcbe72b6-30d6-4e7d-be7f-b0379f1e8b54 · outbound

This paper cites Gen-2, 2023.

Transforming Static Images Using Generative Models for Video Salient Object Detection Gen-2, 2023

Reference 42

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Observation 5086498e-51de-4c47-953b-4458d10cc76a · outbound

This paper cites Kernelized memory network for video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Kernelized memory network for video object segmentation

Reference 43

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Observation fea76d9b-ae68-42c5-9ecc-849f223940df · outbound

This paper cites Hierarchical mem- ory matching network for video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Hierarchical mem- ory matching network for video object segmentation

Reference 44

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Observation 27fa7e9f-f5fd-4dc1-b856-2391c979cb18 · outbound

This paper cites Hierarchical image saliency detection on extended cssd.

Transforming Static Images Using Generative Models for Video Salient Object Detection Hierarchical image saliency detection on extended cssd

Reference 45

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Observation 71ae7345-d348-4d8a-bd61-de3d354d914f · outbound

This paper cites Denoising Diffusion Implicit Models.

Transforming Static Images Using Generative Models for Video Salient Object Detection Denoising Diffusion Implicit Models

Reference 46

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Observation f4acb2a2-6e37-40db-a903-3816120271fa · outbound

This paper cites Improved techniques for training score-based generative models.

Transforming Static Images Using Generative Models for Video Salient Object Detection Improved techniques for training score-based generative models

Reference 47

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Observation 4748fe7c-3e8a-45cf-b279-d4a092bd2033 · outbound

This paper cites Unsupervised video object segmentation with online adversarial self-tuning.

Transforming Static Images Using Generative Models for Video Salient Object Detection Unsupervised video object segmentation with online adversarial self-tuning

Reference 48

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Observation 0274b3d3-2d7c-4785-a84a-e83c41232bcc · outbound

This paper cites A unified transformer frame- work for group-based segmentation: Co-segmentation, co- saliency detection and video salient object detection.

Transforming Static Images Using Generative Models for Video Salient Object Detection A unified transformer frame- work for group-based segmentation: Co-segmentation, co- saliency detection and video salient object detection

Reference 49

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Observation 21e8c68d-96c1-4c39-8fea-19e66b4aa5a3 · outbound

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

Transforming Static Images Using Generative Models for Video Salient Object Detection Raft: Recurrent all-pairs field transforms for optical flow

Reference 50

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Observation 01564162-d1fe-4309-9630-e282d48662a9 · outbound

This paper cites Learning to de- tect salient objects with image-level supervision.

Transforming Static Images Using Generative Models for Video Salient Object Detection Learning to de- tect salient objects with image-level supervision

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:44:08.655777Z

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Observation 6b861226-6ac5-43e9-a6c6-6e4285c32688 · outbound

This paper cites Consistent video saliency using local gradient flow optimization and global refinement.

Transforming Static Images Using Generative Models for Video Salient Object Detection Consistent video saliency using local gradient flow optimization and global refinement

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:44:08.639271Z

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Observation 5e836263-1fd7-4d48-8bbb-fd0b9cde0af8 · outbound

This paper cites Video salient object detection via fully convolutional networks.

Transforming Static Images Using Generative Models for Video Salient Object Detection Video salient object detection via fully convolutional networks

Reference 53

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Observation 4941c26c-ac96-45c5-ab22-3072e9c8dda0 · outbound

This paper cites F3net: fusion, feedback and focus for salient object detection.

Transforming Static Images Using Generative Models for Video Salient Object Detection F3net: fusion, feedback and focus for salient object detection

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T15:44:08.323889Z

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Observation 9cb05069-9ab3-440e-87a2-78c075ca248a · outbound

This paper cites Cbam: Convolutional block attention module.

Transforming Static Images Using Generative Models for Video Salient Object Detection Cbam: Convolutional block attention module

Reference 55

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Observation 170fdbfc-722b-4edd-b4ee-f42585f89283 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transform- ers.

Transforming Static Images Using Generative Models for Video Salient Object Detection Segformer: Simple and efficient design for semantic segmentation with transform- ers

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:44:08.594416Z

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Observation eea1c728-d50f-451e-aba0-dfa6060307c5 · outbound

This paper cites Learning motion-appearance co- attention for zero-shot video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Learning motion-appearance co- attention for zero-shot video object segmentation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:44:08.578731Z

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Observation 2193e3aa-2281-4c0e-b438-2124a734a51f · outbound

This paper cites Anchor diffusion for un- supervised video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Anchor diffusion for un- supervised video object segmentation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:44:08.563339Z

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Observation a446baea-bd8b-4aec-84f2-336cc30fcbc6 · outbound

This paper cites DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory.

Transforming Static Images Using Generative Models for Video Salient Object Detection DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory

Reference 59

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Observation 0fcbb901-1c51-4f91-966c-a4e3bc92121c · outbound

This paper cites I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models.

Transforming Static Images Using Generative Models for Video Salient Object Detection I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models

Reference 60

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Observation a8bb86d3-c105-4eee-b7f0-a7fe6c1dfe7e · outbound

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Transforming Static Images Using Generative Models for Video Salient Object Detection Suppress and balance: A simple gated net- work for salient object detection

Reference 61

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Observation 4742225a-be60-49a3-95be-a7ddf441308a · outbound

This paper cites Learning discriminative feature with crf for unsupervised video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Learning discriminative feature with crf for unsupervised video object segmentation

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-12T15:44:08.360567Z

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Observation 1296c2cf-471d-4922-b28e-c68654b94526 · outbound

This paper cites Motion-attentive transition for zero-shot video object segmentation.

Transforming Static Images Using Generative Models for Video Salient Object Detection Motion-attentive transition for zero-shot video object segmentation

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:44:08.527457Z

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