Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T14:07:17.595684Z
Paper Citation Record · LEDGER
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation
As of 16 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2507.19790.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
58 of 58 outbound references displayed
- verified exact0
- verified fuzzy41
- unresolved17
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation d568c78e-20f8-4986-8c06-ce1a65ef227b · outbound
This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.428365Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db77bd92-1b27-41d5-a7c7-7da198151e85 · outbound
This paper cites Video salient object detection via contrastive features and attention modules.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Video salient object detection via contrastive features and attention modules
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.122856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 767b466f-00f0-4da3-a14b-4a345b693a76 · outbound
This paper cites Global contrast based salient region detection.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Global contrast based salient region detection
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.114243Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 88feef44-2fad-4f8c-aa43-5c46442a7254 · outbound
This paper cites Pixel-level bijective matching for video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Pixel-level bijective matching for video object segmentation
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.105469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a3a37af2-5d0f-4217-899f-a6780df07886 · outbound
This paper cites Tack- ling background distraction in video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Tack- ling background distraction in video object segmentation
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.095728Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e06a9696-655d-4e2f-b889-f712779f728f · outbound
This paper cites Treating mo- tion as option to reduce motion dependency in unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Treating mo- tion as option to reduce motion dependency in unsupervised video object segmentation
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.086724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 68810ba3-876c-470e-8f2f-fc1b3d714868 · outbound
This paper cites Dual pro- totype attention for unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Dual pro- totype attention for unsupervised video object segmentation
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.077606Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 98e36071-c420-48d2-8d91-aeae8b14ff4b · outbound
This paper cites Mevis: A large-scale benchmark for video segmentation with motion expressions.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Mevis: A large-scale benchmark for video segmentation with motion expressions
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.068432Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 568c77ee-3756-4e8b-8005-d8097504f779 · outbound
This paper cites Mose: A new dataset for video object segmentation in complex scenes.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Mose: A new dataset for video object segmentation in complex scenes
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.059813Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2d4170d5-bca5-4d17-93ae-7f68e1a434b8 · outbound
This paper cites Shifting more attention to video salient object detection.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Shifting more attention to video salient object detection
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.457133Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a046de02-e0e3-4f77-a79f-e932242ec377 · outbound
This paper cites Bidirectionally learning dense spatio-temporal feature prop- agation network for unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Bidirectionally learning dense spatio-temporal feature prop- agation network for unsupervised video object segmentation
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.044176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7975eb3b-1b81-4981-9923-ce289566ba2b · outbound
This paper cites Pyramid constrained self- attention network for fast video salient object detection.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Pyramid constrained self- attention network for fast video salient object detection
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.035412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 77d6cfb2-496d-45c9-af82-42d53f0a5b96 · outbound
This paper cites Deep residual learning for image recognition.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Deep residual learning for image recognition
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.026590Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6a3b6f84-9d25-4b1a-a100-9b1e128bafd0 · outbound
This paper cites Simulflow: Simultaneously extracting feature and identifying target for unsupervised video object segmen- tation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Simulflow: Simultaneously extracting feature and identifying target for unsupervised video object segmen- tation
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.018140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 90b9a234-861e-49d0-be21-a511dd3ec936 · outbound
This paper cites Full-duplex strategy for video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Full-duplex strategy for video object segmentation
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:18.009371Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ca426e90-827d-4a47-9993-22e9df10b63f · outbound
This paper cites Casnet: A cross-attention siamese net- work for video salient object detection.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Casnet: A cross-attention siamese net- work for video salient object detection
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.474279Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 67d478dd-0624-4158-9909-9af64e429d90 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Adam: A Method for Stochastic Optimization
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.477152Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0841a068-b03b-4263-97a1-82c17c00307b · outbound
This paper cites Unsupervised video object seg- mentation via prototype memory network.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Unsupervised video object seg- mentation via prototype memory network
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.994764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5eabca7a-1316-4ace-8d79-6618298dc948 · outbound
This paper cites Guided slot attention for unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Guided slot attention for unsupervised video object segmentation
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.986394Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7572b6ea-52a7-4493-a55f-1397f00949ce · outbound
This paper cites Iteratively selecting an easy reference frame makes unsupervised video object segmentation easier.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Iteratively selecting an easy reference frame makes unsupervised video object segmentation easier
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.977740Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2668bdd7-6c2a-44b5-bb2b-47c8d0bfd51f · outbound
This paper cites Video object segmentation with adaptive feature bank and uncertain-region refinement.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Video object segmentation with adaptive feature bank and uncertain-region refinement
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.969143Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 393aac3c-4467-4602-b085-d9ed69c951b9 · outbound
This paper cites F2net: Learning to focus on the foreground for unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation F2net: Learning to focus on the foreground for unsupervised video object segmentation
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.959906Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 27608c3f-3341-44f9-b99c-84e3b08356f4 · outbound
This paper cites Depth-aware test-time training for zero-shot video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Depth-aware test-time training for zero-shot video object segmentation
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.950962Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0f766688-6eed-4f7e-beb0-cea1de3dd734 · outbound
This paper cites See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.942285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 88bfcf9f-993e-460d-8caf-53305a141f78 · outbound
This paper cites Making a Case for 3D Convolutions for Object Segmentation in Videos.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Making a Case for 3D Convolutions for Object Segmentation in Videos
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.500179Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f10d25b5-1cb9-4a03-8caa-a9669c78d1d5 · outbound
This paper cites MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.503258Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ba53732e-4e4a-4d9c-9235-67529619f0dc · outbound
This paper cites Segmentation of moving objects by long term video analysis.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Segmentation of moving objects by long term video analysis
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.933143Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation aee5fc25-4a7a-442e-8f0a-4043a1130077 · outbound
This paper cites Video object segmentation using space-time memory networks.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Video object segmentation using space-time memory networks
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.924618Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4763765c-91d0-4fc5-a0ab-743fcc879d29 · outbound
This paper cites Multi-scale interactive network for salient object detection.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Multi-scale interactive network for salient object detection
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.916188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 006adc3f-e1c0-4325-a1ac-e1a619112591 · outbound
This paper cites Hierarchical feature align- ment network for unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Hierarchical feature align- ment network for unsupervised video object segmentation
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.514792Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c06906a-f6f4-41d5-a030-efebe4900d20 · outbound
This paper cites A benchmark dataset and evaluation methodology for video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation A benchmark dataset and evaluation methodology for video object segmentation
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.520848Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e2bd00b9-51fc-47a3-8d55-417125f0370f · outbound
This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation The 2017 DAVIS Challenge on Video Object Segmentation
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.523677Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7fd2cdf3-9c4c-4319-95fa-f8370d510a5d · outbound
This paper cites Learning object class detectors from weakly annotated video.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Learning object class detectors from weakly annotated video
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.886891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b7fd177f-d545-42b5-83c5-406588da73f6 · outbound
This paper cites Vi- sion transformers for dense prediction.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Vi- sion transformers for dense prediction
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.877432Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4c4b6ab2-ce5c-4a3d-a53e-9e459d98a17a · outbound
This paper cites Reciprocal transformations for unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Reciprocal transformations for unsupervised video object segmentation
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.868589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 24991fed-4798-4885-9a98-762605453d33 · outbound
This paper cites D2conv3d: Dynamic dilated convolutions for object segmentation in videos.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation D2conv3d: Dynamic dilated convolutions for object segmentation in videos
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.859863Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6c63e0bd-e66e-46b2-b273-f3168ac1661e · outbound
This paper cites Hierarchical image saliency detection on extended cssd.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Hierarchical image saliency detection on extended cssd
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.851243Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9c8fd396-d2ba-4ade-8db9-3938d27a68ea · outbound
This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Very Deep Convolutional Networks for Large-Scale Image Recognition
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.541923Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation acbd1e9c-f310-451d-8e9d-096e10c4f057 · outbound
This paper cites Generalizable fourier augmentation for unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Generalizable fourier augmentation for unsupervised video object segmentation
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.842414Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f19a2517-0ad3-47df-abda-60ed15493aaf · outbound
This paper cites Unsupervised video object segmentation with online adversarial self-tuning.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Unsupervised video object segmentation with online adversarial self-tuning
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.548001Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dbfafc47-601b-4c48-9698-ca233e57e76c · outbound
This paper cites A unified transformer frame- work for group-based segmentation: Co-segmentation, co- saliency detection and video salient object detection.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation A unified transformer frame- work for group-based segmentation: Co-segmentation, co- saliency detection and video salient object detection
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.828298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ba5ac20c-3215-4c34-ab3a-9fee9957eeff · outbound
This paper cites Raft: Recurrent all-pairs field transforms for optical flow.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Raft: Recurrent all-pairs field transforms for optical flow
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.553696Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 450f4c19-7205-4357-9888-538826447892 · outbound
This paper cites Video classification with channel-separated convolu- tional networks.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Video classification with channel-separated convolu- tional networks
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.814391Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 27691f2e-7dff-49cc-85bc-010f625f921e · outbound
This paper cites Learning to de- tect salient objects with image-level supervision.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Learning to de- tect salient objects with image-level supervision
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.805058Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 50492449-c98c-497b-ad10-34c95c107926 · outbound
This paper cites Consistent video saliency using local gradient flow optimization and global refinement.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Consistent video saliency using local gradient flow optimization and global refinement
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.562239Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ca62b5e-1e47-4735-9e6b-cab79b2ccaf9 · outbound
This paper cites Zero-shot video object segmenta- tion via attentive graph neural networks.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Zero-shot video object segmenta- tion via attentive graph neural networks
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.790922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation de832e97-b064-4e36-a421-53800942612d · outbound
This paper cites Learning unsupervised video object segmentation through visual attention.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Learning unsupervised video object segmentation through visual attention
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.781960Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 323fb00e-3c25-43cc-abb7-ec3af6b554d8 · outbound
This paper cites F3net: fusion, feedback and focus for salient object detection.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation F3net: fusion, feedback and focus for salient object detection
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.771782Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 492ce512-0a6b-4bf8-b283-05b6f027ee6d · outbound
This paper cites Cbam: Convolutional block attention module.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Cbam: Convolutional block attention module
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.761475Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f86b30db-a889-478c-9d8a-9d80ab6f39bb · outbound
This paper cites Segformer: Simple and efficient design for semantic segmentation with transform- ers.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Segformer: Simple and efficient design for semantic segmentation with transform- ers
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.751551Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7b5bcc91-0d62-4f3d-86ab-eeb56efb11fa · outbound
This paper cites YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.578619Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 581e95c8-e845-4779-96c7-b7202caf15d0 · outbound
This paper cites Learning motion-appearance co- attention for zero-shot video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Learning motion-appearance co- attention for zero-shot video object segmentation
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.741279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8ad05588-d051-4968-a981-ef0bc23023a6 · outbound
This paper cites Anchor diffusion for un- supervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Anchor diffusion for un- supervised video object segmentation
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.731393Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d9f3af9c-2215-418f-a3f3-2495211e5555 · outbound
This paper cites Deep transport network for unsupervised video ob- ject segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Deep transport network for unsupervised video ob- ject segmentation
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.587379Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e03248e-ef00-45e8-a5a6-323d354e3eac · outbound
This paper cites Suppress and balance: A simple gated net- work for salient object detection.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Suppress and balance: A simple gated net- work for salient object detection
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.590170Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 48d581eb-1221-4956-aadb-a531f0039849 · outbound
This paper cites Learning discriminative feature with crf for unsupervised video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Learning discriminative feature with crf for unsupervised video object segmentation
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.710263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation edd71b2a-7021-4005-b968-dd84a24ebbf0 · outbound
This paper cites Motion-attentive transition for zero-shot video object segmentation.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Motion-attentive transition for zero-shot video object segmentation
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:07:17.595684Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dddbf494-cf8f-43d5-9ef7-338359fbbae7 · outbound
This paper cites ii, vi, vii.
DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation ii, vi, vii
Reference 613
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T14:07:17.901497Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.