Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T12:40:28.777686Z
Paper Citation Record · LEDGER
RANet: Ranking Attention Network for Fast Video Object Segmentation
As of 16 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:1908.06647.
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
62 of 62 outbound references displayed
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- verified fuzzy51
- unresolved11
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 436869fc-3af8-400f-b89c-e7caddf60105 · outbound
This paper cites CNN in MRF: Video object segmentation via inference in a CNN-based higher-order spatio-temporal MRF.
RANet: Ranking Attention Network for Fast Video Object Segmentation CNN in MRF: Video object segmentation via inference in a CNN-based higher-order spatio-temporal MRF
Reference 1
- Resolution
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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 66fe5157-54cc-40f3-b789-64d7533d909f · outbound
This paper cites an unresolved cited work.
RANet: Ranking Attention Network for Fast Video Object Segmentation Unresolved cited work
Reference 2
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Source-reported events for the cited work
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Observation a837f97c-fa8b-40a6-94da-5d7a4d3ac575 · outbound
This paper cites One-shot video object segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation One-shot video object segmentation
Reference 3
- Resolution
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Source-reported events for the cited work
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Observation 784a709f-aec5-4277-a165-bc6f2d635ce7 · outbound
This paper cites The 2018 DAVIS Challenge on Video Object Segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation The 2018 DAVIS Challenge on Video Object Segmentation
Reference 4
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 639b4199-21ca-4191-bfc9-c33dc61e0c65 · outbound
This paper cites Semantic image segmentation with deep convolutional nets and fully connected crfs.
RANet: Ranking Attention Network for Fast Video Object Segmentation Semantic image segmentation with deep convolutional nets and fully connected crfs
Reference 5
- Resolution
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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 53cb203d-32a7-47e5-a224-b01d621f8b3e · outbound
This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation
Reference 6
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 422195f9-b1bb-42a9-98fc-ab69f96e46b4 · outbound
This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Encoder-decoder with atrous separable convolution for semantic image segmentation
Reference 7
- Resolution
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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 815c173e-d881-4543-9cfc-271ad0a86699 · outbound
This paper cites Blazingly fast video object segmenta- tion with pixel-wise metric learning.
RANet: Ranking Attention Network for Fast Video Object Segmentation Blazingly fast video object segmenta- tion with pixel-wise metric learning
Reference 8
- Resolution
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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 008e7db8-7b7c-443d-b6f4-785bc44c8673 · outbound
This paper cites Fast and accu- rate online video object segmentation via tracking parts.
RANet: Ranking Attention Network for Fast Video Object Segmentation Fast and accu- rate online video object segmentation via tracking parts
Reference 9
- Resolution
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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 f26f567b-0d4a-4809-9567-46670d94edc1 · outbound
This paper cites Segflow: Joint learning for video object segmentation and optical flow.
RANet: Ranking Attention Network for Fast Video Object Segmentation Segflow: Joint learning for video object segmentation and optical flow
Reference 10
- Resolution
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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 5a695918-4ed6-4ba2-b0d3-bd8975d68ce0 · outbound
This paper cites Mitra, Xiaolei Huang, Philip H.
RANet: Ranking Attention Network for Fast Video Object Segmentation Mitra, Xiaolei Huang, Philip H
Reference 11
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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 254fbb4a-d6e1-47bd-b8f1-fd631b8ae4fa · outbound
This paper cites Flownet: Learning optical flow with convolutional net- works.
RANet: Ranking Attention Network for Fast Video Object Segmentation Flownet: Learning optical flow with convolutional net- works
Reference 12
- Resolution
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Source-reported events for the cited work
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Observation f822ee32-df99-41cf-a215-a5fef2de06fc · outbound
This paper cites Salient ob- jects in clutter: Bringing salient object detection to the foreground.
RANet: Ranking Attention Network for Fast Video Object Segmentation Salient ob- jects in clutter: Bringing salient object detection to the foreground
Reference 13
- Resolution
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Source-reported events for the cited work
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Observation f9aab03d-1cfb-46f7-9575-3bff7d625df0 · outbound
This paper cites Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks.
RANet: Ranking Attention Network for Fast Video Object Segmentation Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks
Reference 14
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Source-reported events for the cited work
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Observation af0a86b8-bdd3-4add-83ca-1518713d2da0 · outbound
This paper cites Shifting more attention to video salient object detection.
RANet: Ranking Attention Network for Fast Video Object Segmentation Shifting more attention to video salient object detection
Reference 15
- Resolution
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Observation c61be777-d9bb-4844-8ceb-18df502c52e4 · outbound
This paper cites Mask r-cnn.
RANet: Ranking Attention Network for Fast Video Object Segmentation Mask r-cnn
Reference 16
- Resolution
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Source-reported events for the cited work
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Observation 9cae2e1f-028b-43ae-8c8c-bf164e2db26b · outbound
This paper cites Deep residual learning for image recognition.
RANet: Ranking Attention Network for Fast Video Object Segmentation Deep residual learning for image recognition
Reference 17
- Resolution
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Source-reported events for the cited work
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Observation 61562311-78e9-4ed0-8b23-4ef337868483 · outbound
This paper cites Norm matters: efficient and accurate nor- malization schemes in deep networks.
RANet: Ranking Attention Network for Fast Video Object Segmentation Norm matters: efficient and accurate nor- malization schemes in deep networks
Reference 18
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation d5912a14-81c2-4ae2-a312-a9105e8ca429 · outbound
This paper cites an unresolved cited work.
RANet: Ranking Attention Network for Fast Video Object Segmentation Unresolved cited work
Reference 19
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Source-reported events for the cited work
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Observation 95a1d9ab-c274-478b-ae6f-6bd96ef9a38a · outbound
This paper cites Flownet 2.0: Evolution of optical flow estimation with deep networks.
RANet: Ranking Attention Network for Fast Video Object Segmentation Flownet 2.0: Evolution of optical flow estimation with deep networks
Reference 20
- Resolution
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Source-reported events for the cited work
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Observation 41398e23-e622-4581-b882-b66fd709e6c7 · outbound
This paper cites Batch normaliza- tion: Accelerating deep network training by reducing internal covariate shift.
RANet: Ranking Attention Network for Fast Video Object Segmentation Batch normaliza- tion: Accelerating deep network training by reducing internal covariate shift
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation a6f292af-7c97-4b30-acfa-2d7c457f0e26 · outbound
This paper cites an unresolved cited work.
RANet: Ranking Attention Network for Fast Video Object Segmentation Unresolved cited work
Reference 22
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Source-reported events for the cited work
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Observation 6b519301-2842-492e-834d-a3ba6b35566f · outbound
This paper cites Online video ob- ject segmentation via convolutional trident network.
RANet: Ranking Attention Network for Fast Video Object Segmentation Online video ob- ject segmentation via convolutional trident network
Reference 23
- Resolution
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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 a9bdfee6-9959-4c2c-a2b8-e267485be676 · outbound
This paper cites Stere- onet: Guided hierarchical refinement for real-time edge-aware depth prediction.
RANet: Ranking Attention Network for Fast Video Object Segmentation Stere- onet: Guided hierarchical refinement for real-time edge-aware depth prediction
Reference 24
- Resolution
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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 c689016d-21fe-49b1-81d9-3201459033ad · outbound
This paper cites Lucid data dreaming for ob- ject tracking.
RANet: Ranking Attention Network for Fast Video Object Segmentation Lucid data dreaming for ob- ject tracking
Reference 25
- Resolution
- verified fuzzy
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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 1814c336-4224-4831-8129-4ed3ca278271 · outbound
This paper cites Adam: A method for stochastic optimization.
RANet: Ranking Attention Network for Fast Video Object Segmentation Adam: A method for stochastic optimization
Reference 26
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Source-reported events for the cited work
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Observation bac6430d-0db8-4337-9f33-e101396042d5 · outbound
This paper cites Hin- ton.
RANet: Ranking Attention Network for Fast Video Object Segmentation Hin- ton
Reference 27
- Resolution
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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 0c7bd8d4-9480-4fd1-ae2b-d2e633e0d3c3 · outbound
This paper cites Instance-level salient object segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Instance-level salient object segmentation
Reference 28
- Resolution
- verified fuzzy
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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 c6f8e4fd-11d2-4f85-8a3e-749b2c9a929c · outbound
This paper cites Visual saliency based on multiscale deep features.
RANet: Ranking Attention Network for Fast Video Object Segmentation Visual saliency based on multiscale deep features
Reference 29
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Source-reported events for the cited work
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Observation 8ef2b370-8e6b-4fed-94c8-5de0acd79bc6 · outbound
This paper cites Video object segmentation with joint re-identification and attention- aware mask propagation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Video object segmentation with joint re-identification and attention- aware mask propagation
Reference 30
- Resolution
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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0f621227-96c2-4e8b-8a62-e84ca65cdfd9 · outbound
This paper cites Refinenet: Multi-path refinement networks for high-resolution semantic segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Refinenet: Multi-path refinement networks for high-resolution semantic segmentation
Reference 31
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Source-reported events for the cited work
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Observation 917d4bd5-57ea-4e05-ad21-0e9ea0932f21 · outbound
This paper cites See more, know more: Unsupervised video object segmentation with co-attention siamese networks.
RANet: Ranking Attention Network for Fast Video Object Segmentation See more, know more: Unsupervised video object segmentation with co-attention siamese networks
Reference 32
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Source-reported events for the cited work
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Observation 332aada8-36c8-43a6-902f-20e077d2e838 · outbound
This paper cites Premvos: Proposal-generation, refinement and merging for the davis challenge on video object segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Premvos: Proposal-generation, refinement and merging for the davis challenge on video object segmentation
Reference 33
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Source-reported events for the cited work
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Observation 77b69059-77b0-4c19-b5c6-0e7d307bbdd0 · outbound
This paper cites Premvos: Proposal-generation, refinement and merging for the youtube-vos challenge on video object segmen- tation 2018.
RANet: Ranking Attention Network for Fast Video Object Segmentation Premvos: Proposal-generation, refinement and merging for the youtube-vos challenge on video object segmen- tation 2018
Reference 34
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Observation 0285b2c1-a3eb-41f1-bf88-d6beb3b373d4 · outbound
This paper cites Premvos: Proposal-generation, refinement and merging for video object segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Premvos: Proposal-generation, refinement and merging for video object segmentation
Reference 35
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Observation 91a09d70-60a8-4186-9194-186a0251720d · outbound
This paper cites Bilateral space video seg- mentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Bilateral space video seg- mentation
Reference 36
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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 e143ad30-048e-402a-83df-cb801b231384 · outbound
This paper cites Video object segmentation without tem- poral information.
RANet: Ranking Attention Network for Fast Video Object Segmentation Video object segmentation without tem- poral information
Reference 37
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b7f1d25a-d1d2-4ca4-b6b4-cec0e6b24d02 · outbound
This paper cites Fast video object segmentation by reference-guided mask propagation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Fast video object segmentation by reference-guided mask propagation
Reference 38
- Resolution
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Source-reported events for the cited work
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Observation e1216a5d-2a74-4ca8-908c-b3948a354181 · outbound
This paper cites Towards bridging semantic gap to improve se- mantic segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Towards bridging semantic gap to improve se- mantic segmentation
Reference 39
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation fdef32a1-1668-4bb2-afd9-8379eda38a97 · outbound
This paper cites Learn- ing video object segmentation from static images.
RANet: Ranking Attention Network for Fast Video Object Segmentation Learn- ing video object segmentation from static images
Reference 40
- Resolution
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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 1c06722d-f414-4771-b6f3-fea108d8dea3 · outbound
This paper cites A benchmark dataset and evaluation method- ology for video object segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation A benchmark dataset and evaluation method- ology for video object segmentation
Reference 41
- Resolution
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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 b93aed7f-8183-4f1f-bf51-ef7bdc431f9b · outbound
This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation The 2017 DAVIS Challenge on Video Object Segmentation
Reference 42
- Resolution
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Source-reported events for the cited work
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Observation 02ac69fc-eb24-4143-9941-8913576088f9 · outbound
This paper cites Deepmatching: Hierarchical deformable dense matching.
RANet: Ranking Attention Network for Fast Video Object Segmentation Deepmatching: Hierarchical deformable dense matching
Reference 43
- Resolution
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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 be746039-5413-40c6-a3f2-c14730ae7553 · outbound
This paper cites U-net: Convolutional networks for biomedical image segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation U-net: Convolutional networks for biomedical image segmentation
Reference 44
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ed0d64f-86ee-4762-82c9-4176f641c8c9 · outbound
This paper cites Pixel-level matching for video object segmentation using convo- lutional neural networks.
RANet: Ranking Attention Network for Fast Video Object Segmentation Pixel-level matching for video object segmentation using convo- lutional neural networks
Reference 45
- Resolution
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Source-reported events for the cited work
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Observation 8540a4e2-7599-4cdd-9eef-b69ed410b935 · outbound
This paper cites Pyramid dilated deeper convlstm for video salient object detection.
RANet: Ranking Attention Network for Fast Video Object Segmentation Pyramid dilated deeper convlstm for video salient object detection
Reference 46
- Resolution
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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 de7933ce-f111-4a1c-84c7-004cd7974f46 · outbound
This paper cites an unresolved cited work.
RANet: Ranking Attention Network for Fast Video Object Segmentation Unresolved cited work
Reference 47
- Resolution
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Source-reported events for the cited work
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Observation cf5887ef-422d-40bf-be1f-3a9c50dbe6c8 · outbound
This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.
RANet: Ranking Attention Network for Fast Video Object Segmentation Instance Normalization: The Missing Ingredient for Fast Stylization
Reference 48
- Resolution
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Source-reported events for the cited work
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Observation 63c8fdaa-f5dd-416e-9136-8e3f7b9eea35 · outbound
This paper cites Feelvos: Fast end-to-end embedding learning for video object seg- mentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Feelvos: Fast end-to-end embedding learning for video object seg- mentation
Reference 49
- Resolution
- verified fuzzy
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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 44152add-9cd4-4173-877d-60f3c50bc2f5 · outbound
This paper cites Online adapta- tion of convolutional neural networks for video object segmentation.
RANet: Ranking Attention Network for Fast Video Object Segmentation Online adapta- tion of convolutional neural networks for video object segmentation
Reference 50
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- raw_fallback, observed 2026-08-14T12:40:29.055758Z
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 0c3c7907-0bb8-4dcc-8431-d9ae6aaec2d6 · outbound
This paper cites Fast online object tracking and seg- mentation: A unifying approach.
RANet: Ranking Attention Network for Fast Video Object Segmentation Fast online object tracking and seg- mentation: A unifying approach
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:29.042191Z
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 06b27769-b3a3-434c-9877-6b379eb124f9 · outbound
This paper cites Zero-shot video object segmen- tation via attentive graph neural networks.
RANet: Ranking Attention Network for Fast Video Object Segmentation Zero-shot video object segmen- tation via attentive graph neural networks
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:29.028160Z
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 8d511774-0d9d-4a05-9783-53c05dad510e · outbound
This paper cites Se- lective video object cutout.
RANet: Ranking Attention Network for Fast Video Object Segmentation Se- lective video object cutout
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:29.014388Z
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 6a247fa8-6c6c-44fb-9ffe-71cc1570f847 · outbound
This paper cites Semi-supervised video object segmen- tation with super-trajectories.
RANet: Ranking Attention Network for Fast Video Object Segmentation Semi-supervised video object segmen- tation with super-trajectories
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:29.000103Z
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 a495ba74-db11-4574-825d-c26638f44a09 · outbound
This paper cites Saliency-aware video object segmenta- tion.
RANet: Ranking Attention Network for Fast Video Object Segmentation Saliency-aware video object segmenta- tion
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:28.985735Z
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 8616ac90-47c4-43ea-a102-eb0127db3480 · outbound
This paper cites Dense residual pyramid networks for salient object detection.
RANet: Ranking Attention Network for Fast Video Object Segmentation Dense residual pyramid networks for salient object detection
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:28.971208Z
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 6413fa24-f209-491e-958d-2f4780b50e99 · outbound
This paper cites Joint detection and identification fea- ture learning for person search.
RANet: Ranking Attention Network for Fast Video Object Segmentation Joint detection and identification fea- ture learning for person search
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:28.955161Z
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 2ad685ac-f7e3-4479-bc18-2fdd73ee601f · outbound
This paper cites Hierar- chical saliency detection.
RANet: Ranking Attention Network for Fast Video Object Segmentation Hierar- chical saliency detection
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:28.941150Z
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 9c74e1f6-ce98-461a-96d3-05a42b1e0e2f · outbound
This paper cites Katsaggelos.
RANet: Ranking Attention Network for Fast Video Object Segmentation Katsaggelos
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:28.926718Z
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 ffa6fb6c-649d-4ad8-91d7-e492663ff232 · outbound
This paper cites Contrast prior and fluid pyramid integration for rgbd salient object detec- tion.
RANet: Ranking Attention Network for Fast Video Object Segmentation Contrast prior and fluid pyramid integration for rgbd salient object detec- tion
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:28.911986Z
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 258f77d6-dfb9-4d81-b111-a39f8b3ce2fd · outbound
This paper cites EGNet: Edge guidance network for salient object detection.
RANet: Ranking Attention Network for Fast Video Object Segmentation EGNet: Edge guidance network for salient object detection
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:40:28.895090Z
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 34a2a23d-dd23-4de5-91ec-afdd77522e47 · outbound
This paper cites an unresolved cited work.
RANet: Ranking Attention Network for Fast Video Object Segmentation Unresolved cited work
Reference 2018
- Resolution
- unresolved
- raw_fallback, observed 2026-08-14T12:40:29.264082Z
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.