A Deep Semantic Segmentation Network with Semantic and Contextual Refinements | Paper Citation Record

Observation d262bb10-27fc-4ad1-9a9d-77dde1b659b6 · outbound

This paper cites SIEDOB: semantic image editing by disentangling object and background,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements SIEDOB: semantic image editing by disentangling object and background,

Reference 1

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Observation c232af57-174d-4202-aa7c-1038910d152a · outbound

This paper cites ASSET: autoregressive semantic scene editing with transformers at high resolutions,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements ASSET: autoregressive semantic scene editing with transformers at high resolutions,

Reference 2

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Observation 691f83be-2899-4f7c-8550-ab5ae9fcf08f · outbound

This paper cites Cross-mix monitoring for medical image segmentation with limited supervision,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Cross-mix monitoring for medical image segmentation with limited supervision,

Reference 3

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Observation 09daecfe-948e-4a87-94d4-aae8fef4bca0 · outbound

This paper cites Portal vein and hepatic vein segmentation in multi-phase MR images using flow-guided change detection,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Portal vein and hepatic vein segmentation in multi-phase MR images using flow-guided change detection,

Reference 4

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Observation a71481de-a1fe-4089-820d-cc82f8d4474b · outbound

This paper cites Multi-target pan-class intrinsic rele- vance driven model for improving semantic segmentation in autonomous driving,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Multi-target pan-class intrinsic rele- vance driven model for improving semantic segmentation in autonomous driving,

Reference 5

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Observation 8e686c3c-6c61-4a01-8223-f68cf9305c18 · outbound

This paper cites Mffenet: Multiscale feature fusion and enhancement network for rgb-thermal urban road scene parsing,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Mffenet: Multiscale feature fusion and enhancement network for rgb-thermal urban road scene parsing,

Reference 6

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Observation d6c808df-9bad-45b5-9f35-bb1bfd8c2473 · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,

Reference 7

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Observation 7eda2945-4a0c-4f98-8e50-c8c2756f10da · outbound

This paper cites Hierarchical Multi-Scale Attention for Semantic Segmentation.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Hierarchical Multi-Scale Attention for Semantic Segmentation

Reference 8

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Observation e705fe00-3486-431b-bc14-62371dbe59a4 · outbound

This paper cites Contour-aware equipotential learning for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Contour-aware equipotential learning for semantic segmentation,

Reference 9

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Observation 6a761cde-4e00-428b-9875-d7e4323eb9dd · outbound

This paper cites Ccnet: Criss-cross attention for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Ccnet: Criss-cross attention for semantic segmentation,

Reference 10

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Observation 149ea8b9-10f7-4262-a70d-71674ee6cabe · outbound

This paper cites Srrnet: A semantic representation refinement network for image segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Srrnet: A semantic representation refinement network for image segmentation,

Reference 11

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Observation b87fb73f-cca4-4ad4-8617-85936ad5a505 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Fully convolutional networks for semantic segmentation,

Reference 12

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Observation 11ee7c9f-11c7-4bc2-afae-4e3a0d79e718 · outbound

This paper cites Large kernel matters– improve semantic segmentation by global convolutional network,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Large kernel matters– improve semantic segmentation by global convolutional network,

Reference 13

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Observation 54cead4d-7f9d-4125-a393-bb6d480f505c · outbound

This paper cites Improving semantic segmentation via video propagation and label relaxation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Improving semantic segmentation via video propagation and label relaxation,

Reference 14

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Observation 5e705d1c-a2be-497e-a974-3a75480aafd7 · outbound

This paper cites Guided upsampling network for real-time semantic seg- mentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Guided upsampling network for real-time semantic seg- mentation,

Reference 15

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Observation f3694af6-cf2a-44e1-b31e-4cf63bd9993b · outbound

This paper cites Decoders matter for semantic segmentation: Data-dependent decoding enables flexible feature aggre- gation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Decoders matter for semantic segmentation: Data-dependent decoding enables flexible feature aggre- gation,

Reference 16

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Observation c916230f-dd9e-47b7-a895-e5776d7e248a · outbound

This paper cites Semantic segmentation network using local relationship upsampling for remote sensing images,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Semantic segmentation network using local relationship upsampling for remote sensing images,

Reference 17

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Observation 20d24aae-1bf3-4289-a4fa-dc1e3026ed8f · outbound

This paper cites Alignseg: Feature-aligned segmentation networks,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Alignseg: Feature-aligned segmentation networks,

Reference 18

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Observation ffc402c5-d2ed-4985-8804-7b259c9af1d4 · outbound

This paper cites Semantic flow for fast and accurate scene parsing,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Semantic flow for fast and accurate scene parsing,

Reference 19

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Observation 7c68926f-6264-4686-8a5e-c344e8bc5b0b · outbound

This paper cites ParseNet: Looking Wider to See Better.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements ParseNet: Looking Wider to See Better

Reference 20

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Observation 4284a0e1-82f5-45bc-8a0d-4ae1c9e413e6 · outbound

This paper cites Pyramid scene parsing network,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Pyramid scene parsing network,

Reference 21

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Observation 8ae62615-a42d-4092-9a54-dbc1ac20a23d · outbound

This paper cites Deep dual-resolution networks for real-time and accurate semantic segmentation of traffic scenes,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Deep dual-resolution networks for real-time and accurate semantic segmentation of traffic scenes,

Reference 22

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Observation 9e444c96-4047-46fa-909e-feb6bf2ec14a · outbound

This paper cites Boundary- guided lightweight semantic segmentation with multi-scale semantic context,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Boundary- guided lightweight semantic segmentation with multi-scale semantic context,

Reference 23

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Observation 10401f21-3314-4f02-8b0d-430adddb871e · outbound

This paper cites Psanet: Point-wise spatial attention network for scene parsing,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Psanet: Point-wise spatial attention network for scene parsing,

Reference 24

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Observation 82292f3b-f3ae-427f-b5d5-763f60e0dc4f · outbound

This paper cites Squeeze-and-excitation networks,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Squeeze-and-excitation networks,

Reference 25

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Observation e09ce04c-964d-4b90-a913-b835b0694415 · outbound

This paper cites Remote sensing semantic segmentation via boundary supervision-aided multiscale chan- nelwise cross attention network,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Remote sensing semantic segmentation via boundary supervision-aided multiscale chan- nelwise cross attention network,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:15.156035Z

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Observation 69042a0a-ecf4-484f-a6f6-53433c50abb0 · outbound

This paper cites A feature refinement module for light-weight semantic segmentation network,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements A feature refinement module for light-weight semantic segmentation network,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:15.133451Z

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Observation a55acec8-7569-494d-8263-7ef9e737d693 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements U-net: Convolutional networks for biomedical image segmentation,

Reference 28

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Observation cc6f3599-4884-4ea1-95df-7f61f07a4c00 · outbound

This paper cites Feature pyramid networks for object detection,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Feature pyramid networks for object detection,

Reference 29

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Observation 0aa8d86c-0474-4ead-9415-954e04974a06 · outbound

This paper cites Segnet: A deep con- volutional encoder-decoder architecture for image segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Segnet: A deep con- volutional encoder-decoder architecture for image segmentation,

Reference 30

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Observation a32adc9b-1d78-4f1f-b40d-4844b84533a5 · outbound

This paper cites Learn- ing implicit feature alignment function for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Learn- ing implicit feature alignment function for semantic segmentation,

Reference 31

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Observation 6da41467-06ee-40dd-8a2f-a972a1c1e7be · outbound

This paper cites High-level feature guided decoding for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements High-level feature guided decoding for semantic segmentation,

Reference 32

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Observation b90fd056-f14a-49f0-b842-7cee665f19b0 · outbound

This paper cites Multi-scale context aggregation by dilated convolutions,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Multi-scale context aggregation by dilated convolutions,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:15.005502Z

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Observation cf724fd7-482d-4b5c-a2e3-672ab29e0928 · outbound

This paper cites Perspective-adaptive convolutions for scene parsing,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Perspective-adaptive convolutions for scene parsing,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.987393Z

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Observation 221e0147-40f6-48f6-92f2-803d25dfd5d6 · outbound

This paper cites Non-local neural networks,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Non-local neural networks,

Reference 35

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Observation 34a6d328-b6e1-44e7-a01b-186823f0b508 · outbound

This paper cites Disentangled non-local neural networks,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Disentangled non-local neural networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.952657Z

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Observation 817bafa5-a9b3-41b9-9ac2-3dcb3ff0f5fa · outbound

This paper cites Context encoding for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Context encoding for semantic segmentation,

Reference 37

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Observation c6718aeb-8c4b-430c-b6ab-2f2ef75c61d7 · outbound

This paper cites Hsnet: An intelligent hierarchical semantic-aware network system for real-time semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Hsnet: An intelligent hierarchical semantic-aware network system for real-time semantic segmentation,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.918013Z

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Observation 80644150-d8c5-418e-b6a8-9ece69b36e1f · outbound

This paper cites Dual attention network for scene segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Dual attention network for scene segmentation,

Reference 39

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Observation 04d5b1f7-fa99-4e11-872a-a89675ed56b5 · outbound

This paper cites Spa- tial transformer networks,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Spa- tial transformer networks,

Reference 40

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Observation 4e517a32-b306-4298-828c-5050b81dc2ec · outbound

This paper cites Exploring cross-image pixel contrast for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Exploring cross-image pixel contrast for semantic segmentation,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.865575Z

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Observation ff760833-d122-4cdb-89ea-dd2c1ca8ace0 · outbound

This paper cites Mix-Domain Contrastive Learning for Unpaired H&E-to-IHC Stain Translation.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Mix-Domain Contrastive Learning for Unpaired H&E-to-IHC Stain Translation

Reference 42

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Observation 125d2fa6-cb1c-4c05-8d59-77f87c73fdf8 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements The cityscapes dataset for semantic urban scene understanding,

Reference 43

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Observation 835b0384-3b12-4546-a9dd-bf9bf602f397 · outbound

This paper cites BDD100K: A diverse driving dataset for heterogeneous JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 13 multitask learning,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements BDD100K: A diverse driving dataset for heterogeneous JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 13 multitask learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.826747Z

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Observation 351912ef-c603-4a87-8a05-c02046a35fc9 · outbound

This paper cites Semantic understanding of scenes through the ADE20K dataset,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Semantic understanding of scenes through the ADE20K dataset,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.805556Z

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Observation 346b46f3-adc1-4cde-8abb-83e31d459deb · outbound

This paper cites Cot: Contourlet transformer for hierarchical semantic segmentation.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Cot: Contourlet transformer for hierarchical semantic segmentation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.784564Z

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Observation 1f2ec6b2-38b1-4fcd-bf5e-70cd474fc469 · outbound

This paper cites A two-stream conditional generative adversarial network for improving semantic predictions in urban driving scenes,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements A two-stream conditional generative adversarial network for improving semantic predictions in urban driving scenes,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.765559Z

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Observation 8f804d1a-2b58-4102-a15c-349dfd852e6b · outbound

This paper cites Segnext: Rethinking convolutional attention design for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Segnext: Rethinking convolutional attention design for semantic segmentation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.747580Z

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Observation d4fdac76-e47c-4034-a5d1-bd80b9ecd722 · outbound

This paper cites Imagenet large scale visual recognition challenge,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Imagenet large scale visual recognition challenge,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.728430Z

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Observation 26440a34-7b37-451a-a3ca-c33c8f02833e · outbound

This paper cites Visual attention network,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Visual attention network,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.709536Z

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Observation db6c350e-f9fb-4774-ae32-d8807c27b72b · outbound

This paper cites Deep high-resolution representation learning for visual recognition,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Deep high-resolution representation learning for visual recognition,

Reference 51

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Observation 3420d858-dfe7-43fe-915d-b1b8c0354e46 · outbound

This paper cites Dynamic neural representa- tional decoders for high-resolution semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Dynamic neural representa- tional decoders for high-resolution semantic segmentation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.680129Z

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Observation 7129a94a-acd1-4ebf-a6fb-110ea34b30f4 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 53

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This paper cites Learning cross-channel repre- sentations for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Learning cross-channel repre- sentations for semantic segmentation,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.641656Z

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Observation 1e05a812-5a53-4760-abf4-884740587a57 · outbound

This paper cites Oneformer: One transformer to rule universal image segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Oneformer: One transformer to rule universal image segmentation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.624089Z

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Observation cdce478e-aca6-4830-a33a-bc13b968d7a6 · outbound

This paper cites Category Feature Transformer for Semantic Segmentation.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Category Feature Transformer for Semantic Segmentation

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:19:14.305986Z

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Observation 671e24ec-5646-4108-a471-48af9e98dc16 · outbound

This paper cites DDP: diffusion model for dense visual prediction,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements DDP: diffusion model for dense visual prediction,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.605550Z

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Observation b71d3110-b68c-401a-9904-3a5e15fd955d · outbound

This paper cites Fast and accurate scene parsing via bi-direction alignment networks,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Fast and accurate scene parsing via bi-direction alignment networks,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.588548Z

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Observation b9d48cf1-c8cc-4c69-bf31-73853eca8a36 · outbound

This paper cites Stage-aware feature alignment network for real-time semantic segmentation of street scenes,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Stage-aware feature alignment network for real-time semantic segmentation of street scenes,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.568303Z

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Observation 6618e551-7f7f-4b74-8c04-4121223dff68 · outbound

This paper cites Rtformer: Efficient design for real-time semantic segmentation with transformer,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Rtformer: Efficient design for real-time semantic segmentation with transformer,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.551850Z

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Observation bab2e078-f344-41cc-ba93-bf72513d7715 · outbound

This paper cites Prseg: A lightweight patch rotate MLP decoder for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Prseg: A lightweight patch rotate MLP decoder for semantic segmentation,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.534926Z

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Observation c2ec9d6e-29a9-47c2-a5f5-85bdb2d61963 · outbound

This paper cites Pidnet: A real-time semantic segmentation network inspired by PID controllers,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Pidnet: A real-time semantic segmentation network inspired by PID controllers,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.516894Z

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Observation 0459f699-703f-4ae9-aab5-27e6228bad6c · outbound

This paper cites Sctnet: Single- branch cnn with transformer semantic information for real-time seg- mentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Sctnet: Single- branch cnn with transformer semantic information for real-time seg- mentation,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.497255Z

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Observation 6c06ae9f-263c-4069-b1b7-d68d1e55e83f · outbound

This paper cites Cars can’t fly up in the sky: Improving urban-scene segmentation via height-driven attention networks,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Cars can’t fly up in the sky: Improving urban-scene segmentation via height-driven attention networks,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.475664Z

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Observation 074ff583-0938-4011-a099-c75ecceaa08d · outbound

This paper cites Pointflow: Flowing semantics through points for aerial image segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Pointflow: Flowing semantics through points for aerial image segmentation,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.455729Z

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Observation 1f7d0396-0801-46fe-acfc-b55d64eef3f0 · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.432516Z

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Observation 8edf74ac-0d85-4331-a860-566174281ab8 · outbound

This paper cites Semask: Semantically masked transformers for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Semask: Semantically masked transformers for semantic segmentation,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.410920Z

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Observation ac65cd1a-e7d0-4f75-9506-415ef4a09b06 · outbound

This paper cites Efficient self-ensemble for semantic segmentation,.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Efficient self-ensemble for semantic segmentation,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:19:14.389702Z

Source-reported events for the cited work

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Observation befdd507-d0e0-4f1a-872a-632ddc7ebc46 · outbound

This paper cites ICPC: Instance-Conditioned Prompting with Contrastive Learning for Semantic Segmentation.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements ICPC: Instance-Conditioned Prompting with Contrastive Learning for Semantic Segmentation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T18:19:14.196849Z

Source-reported events for the cited work

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Observation 70151216-c5a9-4e63-b00d-b8dc31a05e09 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

A Deep Semantic Segmentation Network with Semantic and Contextual Refinements Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T18:19:14.202460Z

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