EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation | Paper Citation Record

Observation 8a66ec0e-c06d-4282-bb1c-6f05655d3012 · outbound

This paper cites Ev-segnet: Semantic segmentation for event-based cameras,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Ev-segnet: Semantic segmentation for event-based cameras,

Reference 1

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Observation b802450d-5456-4f20-8f38-bfd2897fe740 · outbound

This paper cites Shapeconv: Shape-aware convolutional layer for indoor rgb-d semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Shapeconv: Shape-aware convolutional layer for indoor rgb-d semantic segmentation,

Reference 2

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Observation 5ce17998-7b8b-4695-8264-84e38501be80 · outbound

This paper cites Bi-directional cross-modality feature propagation with separation-and-aggregation gate for rgb-d semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Bi-directional cross-modality feature propagation with separation-and-aggregation gate for rgb-d semantic segmentation,

Reference 3

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Observation f3a5c34e-31f4-4dc9-a512-2a466eeec073 · outbound

This paper cites Event-based semantic segmentation with posterior attention,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Event-based semantic segmentation with posterior attention,

Reference 4

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Observation 590ec1ea-639b-42b6-8e13-3a0cc692bc6f · outbound

This paper cites Rtfnet: Rgb-thermal fusion network for semantic segmentation of urban scenes,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Rtfnet: Rgb-thermal fusion network for semantic segmentation of urban scenes,

Reference 5

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Observation c2bb04ee-4b55-411a-8441-fb5389ec28f1 · outbound

This paper cites Delivering arbitrary-modal semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Delivering arbitrary-modal semantic segmentation,

Reference 6

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Observation a01a1f47-82be-43db-b868-5d97d38c420b · outbound

This paper cites OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of All.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of All

Reference 7

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Observation 9cf9c232-6995-48e2-a0cf-257364f9a713 · outbound

This paper cites Fusenet: Incorporating depth into semantic segmentation via fusion-based cnn architecture,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Fusenet: Incorporating depth into semantic segmentation via fusion-based cnn architecture,

Reference 8

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Observation 46d97b7b-036a-4641-9d41-dd9160e40c98 · outbound

This paper cites Rgb and lidar fusion based 3d semantic seg- mentation for autonomous driving,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Rgb and lidar fusion based 3d semantic seg- mentation for autonomous driving,

Reference 9

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Observation 75420593-0d46-405a-8e72-02e749318d08 · outbound

This paper cites Mseg3d: Multi-modal 3d semantic segmentation for autonomous driving,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Mseg3d: Multi-modal 3d semantic segmentation for autonomous driving,

Reference 10

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Observation d21005d1-51e3-4a3a-9a1d-391c8e76c929 · outbound

This paper cites Unibind: Llm-augmented unified and balanced representation space to bind them all,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Unibind: Llm-augmented unified and balanced representation space to bind them all,

Reference 11

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Observation abbfa9ee-810c-4a0b-9c07-b2aed605584c · outbound

This paper cites Sam-event-adapter: Adapting segment anything model for event-rgb semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Sam-event-adapter: Adapting segment anything model for event-rgb semantic segmentation,

Reference 12

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Observation df2c3feb-2416-4730-bfc9-b5d681b663cf · outbound

This paper cites Eseg: Event-based segmentation boosted by explicit edge- semantic guidance,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Eseg: Event-based segmentation boosted by explicit edge- semantic guidance,

Reference 13

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Observation b4d50818-3838-48ed-9e00-7ad3ace12953 · outbound

This paper cites Eventdance: Unsupervised source-free cross-modal adaptation for event-based object recognition,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Eventdance: Unsupervised source-free cross-modal adaptation for event-based object recognition,

Reference 14

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Observation 9fdc5b25-b3db-441d-9385-fcd759fd57be · outbound

This paper cites Exact: Language-guided conceptual reasoning and uncertainty estimation for event-based action recognition and more,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Exact: Language-guided conceptual reasoning and uncertainty estimation for event-based action recognition and more,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:40.136570Z

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Observation 6077fd7c-9873-4cc0-bf1a-759d447d5135 · outbound

This paper cites Cafuser: Condition-aware multimodal fusion for robust semantic perception of driving scenes,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Cafuser: Condition-aware multimodal fusion for robust semantic perception of driving scenes,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:39.986562Z

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Observation 1d22fb93-76f4-486f-876b-e098bc36075e · outbound

This paper cites StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation

Reference 17

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Observation f6f33232-fff2-4e43-b3a5-8a1edaad5d2e · outbound

This paper cites Centering the value of every modality: Towards efficient and resilient modality-agnostic semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Centering the value of every modality: Towards efficient and resilient modality-agnostic semantic segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:39.849623Z

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Observation 906c958f-4da5-445a-bcc0-09988b03394b · outbound

This paper cites Multimodal token fusion for vision transformers,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Multimodal token fusion for vision transformers,

Reference 19

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Observation 1849608d-46cd-4aa7-8a69-bb5dd6c5a2b7 · outbound

This paper cites 360sfuda++: Towards source-free uda for panoramic segmentation by learning reliable category prototypes,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation 360sfuda++: Towards source-free uda for panoramic segmentation by learning reliable category prototypes,

Reference 20

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Observation 654cf705-dc39-43a7-b89f-a2395b77b0d3 · outbound

This paper cites Semantics distortion and style matter: Towards source-free uda for panoramic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Semantics distortion and style matter: Towards source-free uda for panoramic segmentation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:39.406412Z

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Observation 729e770d-5f1f-439c-be19-ae2a87cdd7e5 · outbound

This paper cites Both style and distortion matter: Dual- path unsupervised domain adaptation for panoramic semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Both style and distortion matter: Dual- path unsupervised domain adaptation for panoramic semantic segmentation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:39.272199Z

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Observation 6c2c6ce8-3eca-4534-9963-470a8870b833 · outbound

This paper cites Look at the neighbor: Distortion-aware unsupervised domain adaptation for panoramic semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Look at the neighbor: Distortion-aware unsupervised domain adaptation for panoramic semantic segmentation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:39.135517Z

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Observation 0fbd33c4-7342-4ab5-884f-28e1cd43ae31 · outbound

This paper cites Multimodal material segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Multimodal material segmentation,

Reference 24

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Observation d41e81c4-716f-4a01-adc1-bf7f3d458fa6 · outbound

This paper cites Multi-shot temporal event localization: A benchmark,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Multi-shot temporal event localization: A benchmark,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:38.616643Z

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Observation 0b9210d6-54ba-4408-9be9-871a0d21566c · outbound

This paper cites Beyond rgb: Very high resolution urban remote sensing with multimodal deep networks,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Beyond rgb: Very high resolution urban remote sensing with multimodal deep networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:38.414754Z

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Observation 14e8e53e-c353-477b-99e6-544783d55765 · outbound

This paper cites U-net ensemble for enhanced semantic segmentation in remote sensing imagery,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation U-net ensemble for enhanced semantic segmentation in remote sensing imagery,

Reference 27

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Observation f76f8d3e-e85e-4326-9b70-15ef2a7bf59f · outbound

This paper cites Metasegnet: Metadata-collaborative vision-language representation learning for semantic segmentation of remote sensing images,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Metasegnet: Metadata-collaborative vision-language representation learning for semantic segmentation of remote sensing images,

Reference 28

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Observation 19b1a5eb-bd13-4f90-9bdc-8ad2e386c0bd · outbound

This paper cites Transformer-cnn cohort: Semi-supervised semantic segmentation by the best of both students,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Transformer-cnn cohort: Semi-supervised semantic segmentation by the best of both students,

Reference 29

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Observation 29a21184-eedf-4777-ad94-908eb06f3149 · outbound

This paper cites Distilling efficient vision transformers from cnns for semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Distilling efficient vision transformers from cnns for semantic segmentation,

Reference 30

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Observation 4591c939-a97e-44a6-9d65-758487e655f7 · outbound

This paper cites Frozen is better than learning: A new design of prototype-based classifier for semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Frozen is better than learning: A new design of prototype-based classifier for semantic segmentation,

Reference 31

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Observation 53ba671e-4153-4bbc-a885-c0ef7d5b7b32 · outbound

This paper cites Covered: Collaborative robot environment dataset for 3d semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Covered: Collaborative robot environment dataset for 3d semantic segmentation,

Reference 32

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Observation ed175693-ed6e-4d32-95fe-1dda2d0b7648 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Fully convolutional networks for semantic segmentation,

Reference 33

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Observation 47bc5df0-e6a7-453e-9987-2d9f839124e8 · outbound

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

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:36.424744Z

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Observation 76bec327-c689-4f56-870d-1895c79bc415 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Encoder-decoder with atrous separable convolution for semantic image segmentation,

Reference 35

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Observation d5510f49-f132-4429-a1a8-24b9141e8f9a · outbound

This paper cites Strip pooling: Rethinking spatial pooling for scene pars- ing,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Strip pooling: Rethinking spatial pooling for scene pars- ing,

Reference 36

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Observation 6903c915-77e3-4334-879a-6ded3dec6597 · outbound

This paper cites Pyramid scene parsing network,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Pyramid scene parsing network,

Reference 37

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Observation d480ac81-ab70-4009-b2cd-ac816670a632 · outbound

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

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Cars can’t fly up in the sky: Improving urban-scene segmen- tation via height-driven attention networks,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:35.614937Z

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Observation 92d355b4-398a-47c8-8c60-463d691b697f · outbound

This paper cites Dual attention network for scene segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Dual attention network for scene segmentation,

Reference 39

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Observation c79142b0-867e-4ea1-94b0-1222503d3d75 · outbound

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

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Ccnet: Criss-cross attention for semantic segmentation,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:35.290124Z

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Observation 3afe158c-4e6e-4c07-a019-0d4b862520d2 · outbound

This paper cites Ocnet: Object context for semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Ocnet: Object context for semantic segmentation,

Reference 41

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Observation 7315b37d-8e75-41e9-9eae-ebcf55fbd7c0 · outbound

This paper cites Inverseform: A loss function for structured boundary-aware segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Inverseform: A loss function for structured boundary-aware segmentation,

Reference 42

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Observation 33464a97-6933-4e7c-a888-90b3741023e2 · outbound

This paper cites Boundary-aware feature propagation for scene segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Boundary-aware feature propagation for scene segmentation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:34.844907Z

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Observation 6a7c3037-c79a-4c64-92ee-e5724f1e03a1 · outbound

This paper cites Improving semantic segmentation via decoupled body and edge supervision,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Improving semantic segmentation via decoupled body and edge supervision,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:34.612020Z

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Observation bac542c9-a8da-449d-9fd4-cfff72843407 · outbound

This paper cites MlTr: Multi-label Classification with Transformer.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation MlTr: Multi-label Classification with Transformer

Reference 45

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Observation c6652629-e761-45f7-b42c-1ba888870863 · outbound

This paper cites Multi- scale high-resolution vision transformer for semantic segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Multi- scale high-resolution vision transformer for semantic segmentation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:34.375561Z

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Observation 67a19b09-c1fc-4e3a-9c0f-dda4b6712f1f · outbound

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

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Segnext: Rethinking convolutional attention design for semantic segmentation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:34.158848Z

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Observation 7babdc00-a427-45ca-aabb-469d62fd7a3a · outbound

This paper cites Swin transformer v2: Scaling up capacity and resolution,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Swin transformer v2: Scaling up capacity and resolution,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:34.026301Z

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Observation 8ff00dc9-0660-4ff0-913f-9e39a115d27c · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:33.835479Z

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Observation d4edc1c9-213e-4035-90a5-c8239dc1c2f6 · outbound

This paper cites Segmenter: Transformer for semantic segmen- tation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Segmenter: Transformer for semantic segmen- tation,

Reference 50

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

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 51

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EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Segvit: Semantic segmenta- tion with plain vision transformers,

Reference 52

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This paper cites Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers,

Reference 53

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This paper cites X- align: Cross-modal cross-view alignment for bird’s-eye-view segmentation,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation X- align: Cross-modal cross-view alignment for bird’s-eye-view segmentation,

Reference 54

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This paper cites Modality-induced transfer-fusion network for rgb-d and rgb-t salient object detection,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Modality-induced transfer-fusion network for rgb-d and rgb-t salient object detection,

Reference 55

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This paper cites Bridging search region interaction with template for rgb-t tracking,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Bridging search region interaction with template for rgb-t tracking,

Reference 56

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This paper cites Cross-collaborative fusion-encoder network for robust rgb-thermal salient object detection,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Cross-collaborative fusion-encoder network for robust rgb-thermal salient object detection,

Reference 57

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This paper cites Glass segmentation using intensity and spectral polarization cues,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Glass segmentation using intensity and spectral polarization cues,

Reference 58

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This paper cites Caver: Cross-modal view-mixed transformer for bi- modal salient object detection,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Caver: Cross-modal view-mixed transformer for bi- modal salient object detection,

Reference 59

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This paper cites Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness

Reference 60

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This paper cites Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization

Reference 61

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This paper cites MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation

Reference 62

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This paper cites Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

Reference 63

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This paper cites Learning modality-agnostic representation for semantic segmentation from any modalities,.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Learning modality-agnostic representation for semantic segmentation from any modalities,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:31.579638Z

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This paper cites MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection

Reference 65

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This paper cites Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts

Reference 66

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This paper cites Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks.

EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks

Reference 67

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