DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation | Paper Citation Record

Observation b361bdf7-44c8-432a-8133-9c583ac4cafe · outbound

This paper cites Combining labeled and un- labeled data with co-training.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Combining labeled and un- labeled data with co-training

Reference 1

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Observation 90224317-0175-49c4-9559-9181ffc487fb · outbound

This paper cites Semi-supervised medical image segmentation via learning consistency under transformations.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Semi-supervised medical image segmentation via learning consistency under transformations

Reference 2

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Observation bbbb4192-5935-4745-a7ad-a4a3d62653ab · outbound

This paper cites End-to- end object detection with transformers.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation End-to- end object detection with transformers

Reference 3

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Observation 930599fe-7d72-456a-b7cb-68c8e34301f2 · outbound

This paper cites Panoptic segmentation on panoramic radiographs: Deep learning-based segmentation of various structures including maxillary sinus and mandibu- lar canal.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Panoptic segmentation on panoramic radiographs: Deep learning-based segmentation of various structures including maxillary sinus and mandibu- lar canal

Reference 4

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Observation 82129577-c85f-4c9c-903c-2da88c0f94c5 · outbound

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

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 5

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Observation 5ab76188-31ce-411e-b709-32764ffe1b0d · outbound

This paper cites Naive-student: Leveraging semi-supervised learning in video sequences for urban scene segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Naive-student: Leveraging semi-supervised learning in video sequences for urban scene segmentation

Reference 6

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Observation 0f87586f-ac8a-49bd-9cb3-04e0adbb1478 · outbound

This paper cites Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation

Reference 7

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Observation c0446866-c543-4c2c-992f-a48e4cfaf7b8 · outbound

This paper cites Per- pixel classification is not all you need for semantic segmen- tation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Per- pixel classification is not all you need for semantic segmen- tation

Reference 8

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Observation 85cd13e2-a77f-4cbd-b490-908a98b29231 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Masked-attention mask transformer for universal image segmentation

Reference 9

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Observation 1a245ef6-aa66-4a55-957c-4aab68b0ab17 · outbound

This paper cites Reproducible scal- ing laws for contrastive language-image learning.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Reproducible scal- ing laws for contrastive language-image learning

Reference 10

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Observation 2d5526c1-ad16-4a71-831c-01652191dffc · outbound

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

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation The cityscapes dataset for semantic urban scene understanding

Reference 11

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Observation 6b33369a-bd5d-4d02-abe9-9b4763b75f94 · outbound

This paper cites Panoptic segmentation meets remote sensing.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Panoptic segmentation meets remote sensing

Reference 12

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Observation e9f5d4c7-705c-44eb-8aeb-ac7888c30e58 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Imagenet: A large-scale hierarchical image database

Reference 13

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Observation 19722d0b-8304-45e5-bb3a-77c26c6fcbcf · outbound

This paper cites De- coupling zero-shot semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation De- coupling zero-shot semantic segmentation

Reference 14

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Observation c35343ef-75b6-49e7-9ea9-35f94d73fecf · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation An image is worth 16x16 words: Transformers for image recognition at scale

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.810154Z

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Observation f0f4a7d6-37c9-4004-b9e6-9e63e8cf3d26 · outbound

This paper cites Finlayson.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Finlayson

Reference 16

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Observation 3c41cb25-0472-4f7b-a5b1-bb3427a2bd82 · outbound

This paper cites Scal- ing open-vocabulary image segmentation with image-level labels.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Scal- ing open-vocabulary image segmentation with image-level labels

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.775449Z

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Observation 4699822a-1d57-48f9-88a8-94ae985e9ec2 · outbound

This paper cites Generative adversarial nets.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Generative adversarial nets

Reference 18

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Observation 3e1d5439-6826-443f-b254-f04f01f75f1c · outbound

This paper cites Revisit- ing consistency for semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Revisit- ing consistency for semi-supervised semantic segmentation

Reference 19

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Observation 4b570715-47e7-411f-9c65-0fc2a16ec1bf · outbound

This paper cites Open-vocabulary object detection via vision and language knowledge distillation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Open-vocabulary object detection via vision and language knowledge distillation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.728047Z

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Observation 08a1eab8-e960-4266-a2b3-56f372f706de · outbound

This paper cites Mask r-cnn.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Mask r-cnn

Reference 21

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Observation dd55f28c-8d7c-4e14-b9e7-b800b0ebce1d · outbound

This paper cites Semivl: Semi- supervised semantic segmentation with vision-language guidance.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Semivl: Semi- supervised semantic segmentation with vision-language guidance

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.699812Z

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Observation 335deb0f-21cc-4566-b134-c335d8695a3e · outbound

This paper cites Semi-supervised semantic segmentation via adaptive equalization learning.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Semi-supervised semantic segmentation via adaptive equalization learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.681777Z

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Observation 0da0a285-e54f-4b0e-822f-1014b0443135 · outbound

This paper cites Pseudo-label alignment for semi-supervised instance segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Pseudo-label alignment for semi-supervised instance segmentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.663917Z

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Observation d64b1897-6c49-4614-9f46-6b8c775d99d4 · outbound

This paper cites Training vision transformers for semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Training vision transformers for semi-supervised semantic segmentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.646100Z

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Observation 2f62f07e-006f-4bdd-9a73-69472042aada · outbound

This paper cites Scaling up visual and vision-language representa- tion learning with noisy text supervision.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 26

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Observation f44f6e1a-0e67-47b1-ae42-da1dbaae50aa · outbound

This paper cites Learning mask-aware clip representations for zero-shot segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Learning mask-aware clip representations for zero-shot segmentation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.617880Z

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Observation 47d9f710-169f-4e71-9d4f-0db0946c190b · outbound

This paper cites A three- stage self-training framework for semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation A three- stage self-training framework for semi-supervised semantic segmentation

Reference 28

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Observation 68718701-15d8-4fb3-a947-ce8229fabcc8 · outbound

This paper cites Kingma and Jimmy Ba.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Kingma and Jimmy Ba

Reference 29

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Observation 1a2c6938-b82a-460d-9b1f-2e49f6751da2 · outbound

This paper cites Panoptic feature pyramid networks.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Panoptic feature pyramid networks

Reference 30

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Observation ca32aa36-fadc-4d99-8a0f-33d3c780d728 · outbound

This paper cites Panoptic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Panoptic segmentation

Reference 31

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Observation c6f00b17-2324-4109-9b5b-60102cb8ab19 · outbound

This paper cites Segment any- thing.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Segment any- thing

Reference 32

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Observation 283658a3-27c2-4870-a8bd-56df91ddaff6 · outbound

This paper cites Open-vocabulary object detection upon frozen vision and language models.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Open-vocabulary object detection upon frozen vision and language models

Reference 33

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Observation a815447d-60cf-430e-8391-c5bff841f065 · outbound

This paper cites Semi-supervised learning for optical flow with generative ad- versarial networks.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Semi-supervised learning for optical flow with generative ad- versarial networks

Reference 34

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Observation c3718dae-f3ec-47ae-936e-96b123f544bf · outbound

This paper cites Semi-supervised semantic seg- mentation with directional context-aware consistency.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Semi-supervised semantic seg- mentation with directional context-aware consistency

Reference 35

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Observation c6620e22-446e-4d39-8ae3-ccdf26c4c3f5 · outbound

This paper cites Proxyclip: Proxy at- tention improves clip for open-vocabulary segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Proxyclip: Proxy at- tention improves clip for open-vocabulary segmentation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.463134Z

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Observation fa3ecb24-e504-4079-9ec7-a5a1b6e79e23 · outbound

This paper cites Language-driven semantic seg- mentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Language-driven semantic seg- mentation

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.445984Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8906157f-6170-49a9-a881-138f6f2292e2 · outbound

This paper cites Mask dino: Towards a unified transformer-based framework for object detection and segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Mask dino: Towards a unified transformer-based framework for object detection and segmentation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.429461Z

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Observation 5dc9036a-38e8-4330-afab-e95c77bdf9aa · outbound

This paper cites Weakly-and semi-supervised panoptic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Weakly-and semi-supervised panoptic segmentation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.412975Z

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Observation 82acad3a-e077-4323-a5bb-48b0f451fee1 · outbound

This paper cites Logic-induced diagnostic reasoning for semi-supervised se- mantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Logic-induced diagnostic reasoning for semi-supervised se- mantic segmentation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.396114Z

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Observation 4cf9b83f-f26c-4338-855f-8594a3de382c · outbound

This paper cites Open-vocabulary semantic segmentation with mask-adapted clip.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Open-vocabulary semantic segmentation with mask-adapted clip

Reference 41

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Observation 662187a7-a1b0-4d30-a286-b8d05690ce35 · outbound

This paper cites Microsoft coco: Common objects in context.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Microsoft coco: Common objects in context

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.363085Z

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Observation f0206a27-8b66-465d-a261-1ad4cb431743 · outbound

This paper cites A convnet for the 2020s.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation A convnet for the 2020s

Reference 43

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Source-reported events for the cited work

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Observation eae3295d-8251-4002-b606-ea4ce6f27d45 · outbound

This paper cites Decoupled weight decay regularization.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Decoupled weight decay regularization

Reference 44

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Observation 39e29699-2513-475b-9c9b-1e16dace201a · outbound

This paper cites Rankmatch: Exploring the better consistency regularization for semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Rankmatch: Exploring the better consistency regularization for semi-supervised semantic segmentation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.313496Z

Source-reported events for the cited work

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Observation aa7233e2-b681-497a-b2d8-8b3bd0abe9b2 · outbound

This paper cites Mc-panda: Mask confidence for panoptic domain adaptation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Mc-panda: Mask confidence for panoptic domain adaptation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.292512Z

Source-reported events for the cited work

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Observation aef5c156-85fc-418e-a37f-fdd1e220e6fc · outbound

This paper cites Semi-supervised semantic segmentation with high-and low- level consistency.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Semi-supervised semantic segmentation with high-and low- level consistency

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.272946Z

Source-reported events for the cited work

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Observation 7e20edb8-9693-4312-ae54-00a3dfe4cf00 · outbound

This paper cites Semi- supervised semantic segmentation with cross-consistency training.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Semi- supervised semantic segmentation with cross-consistency training

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.254045Z

Source-reported events for the cited work

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Observation 8f3d3a43-b5c3-4cc3-9b5a-ccff71e21f62 · outbound

This paper cites Ca-ssl: Class-agnostic semi-supervised learning for detection and segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Ca-ssl: Class-agnostic semi-supervised learning for detection and segmentation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.234876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d8302b82-632b-4ec8-81ab-996f264bf9c0 · outbound

This paper cites Ke- gan: Knowledge embedded generative adversarial networks for semi-supervised scene parsing.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Ke- gan: Knowledge embedded generative adversarial networks for semi-supervised scene parsing

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.209273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 11eacc00-7792-46a6-82eb-36218a6dfccd · outbound

This paper cites Deep co-training for semi-supervised image recogni- tion.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Deep co-training for semi-supervised image recogni- tion

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.190068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c552f4eb-82be-44ad-8218-0342db06757f · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Learning transferable visual models from natural language supervi- sion

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.170673Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8b416c57-c8e4-46f6-88d9-63e02455f6f1 · outbound

This paper cites Zero-shot text-to-image generation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Zero-shot text-to-image generation

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T17:44:34.344012Z

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Observation 95775793-30a7-43be-a28f-fb20599e6409 · outbound

This paper cites Imagenet-21k pretraining for the masses.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Imagenet-21k pretraining for the masses

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.137966Z

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Observation 8de76a8f-dd50-453a-bd53-4b6115b364c4 · outbound

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

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation High-resolution image synthesis with latent diffusion models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T17:44:34.353778Z

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Observation f29f867e-9493-4e2a-83c3-8ffe1ddbce7f · outbound

This paper cites Acdc: The adverse conditions dataset with correspondences for se- mantic driving scene understanding.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Acdc: The adverse conditions dataset with correspondences for se- mantic driving scene understanding

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.105872Z

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Observation bd1dd81b-a93e-4772-adb0-26d6e8565998 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.085946Z

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Observation 90aa336b-db1f-47a4-902d-af1d7a642a7d · outbound

This paper cites Fixmatch: Simplifying semi- supervised learning with consistency and confidence.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Fixmatch: Simplifying semi- supervised learning with consistency and confidence

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.066702Z

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Observation f9931d57-fe23-4f44-8116-1b6e29c08a5a · outbound

This paper cites Semi supervised semantic segmentation using generative ad- versarial network.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Semi supervised semantic segmentation using generative ad- versarial network

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.048689Z

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Observation 955352ae-8d08-486f-a5df-12a23431cefa · outbound

This paper cites Corrmatch: Label propagation via correlation matching for semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Corrmatch: Label propagation via correlation matching for semi-supervised semantic segmentation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.029332Z

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Observation 91af3113-f98d-4b45-a96f-7b83402107ed · outbound

This paper cites Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:35.009090Z

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Observation cd70d10b-8b0c-4639-bdb4-640c3954fd60 · outbound

This paper cites Attention is all you need.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Attention is all you need

Reference 62

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Observation 7aaef5ac-0b6b-40cf-8854-073e8a07d1f9 · outbound

This paper cites Sclip: Rethink- ing self-attention for dense vision-language inference.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Sclip: Rethink- ing self-attention for dense vision-language inference

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.976290Z

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Observation 1ca82406-98a5-4ef7-ab31-acf8a1269817 · outbound

This paper cites Max-deeplab: End-to-end panoptic segmentation with mask transformers.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Max-deeplab: End-to-end panoptic segmentation with mask transformers

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.953248Z

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Observation d10f5bf0-8b80-423e-a28e-8b3dcaac7405 · outbound

This paper cites Allspark: Reborn labeled features from unlabeled in trans- former for semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Allspark: Reborn labeled features from unlabeled in trans- former for semi-supervised semantic segmentation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.934247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation be776ea6-0f84-472d-abdf-ba8dce425dea · outbound

This paper cites Towards the uncharted: Density-descending feature perturbation for semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Towards the uncharted: Density-descending feature perturbation for semi-supervised semantic segmentation

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.913843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2084ac42-65ca-4442-8b13-7bba150bff52 · outbound

This paper cites Robust fine-tuning of zero-shot models.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Robust fine-tuning of zero-shot models

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.896615Z

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Observation 1b1f272d-9fe8-411a-ba21-732779263fc1 · outbound

This paper cites Querying labeled for unlabeled: Cross- image semantic consistency guided semi-supervised seman- tic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Querying labeled for unlabeled: Cross- image semantic consistency guided semi-supervised seman- tic segmentation

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.878479Z

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Observation 06eaa324-48f8-4170-a3e4-f50640577a09 · outbound

This paper cites Unsupervised data augmentation for consistency training.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Unsupervised data augmentation for consistency training

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.856861Z

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Observation ed9b11b8-4a1d-421e-a1ad-c94f94c64c21 · outbound

This paper cites Open-vocabulary panop- tic segmentation with text-to-image diffusion models.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Open-vocabulary panop- tic segmentation with text-to-image diffusion models

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.837507Z

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Observation acbbd30f-dea5-45ee-b4b5-f72271d48db7 · outbound

This paper cites End-to- end semi-supervised object detection with soft teacher.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation End-to- end semi-supervised object detection with soft teacher

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.818651Z

Source-reported events for the cited work

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Observation 1005287d-7d63-4b44-b655-497ee590e8e1 · outbound

This paper cites Vid2seq: Large-scale pretraining of a vi- sual language model for dense video captioning.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Vid2seq: Large-scale pretraining of a vi- sual language model for dense video captioning

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.800561Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f504b26d-18f4-46d6-b919-d2529c175e2e · outbound

This paper cites St++: Make self-training work better for semi-supervised se- mantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation St++: Make self-training work better for semi-supervised se- mantic segmentation

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.783022Z

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Observation 6620c6c0-5085-4592-9b48-cbe027d388d1 · outbound

This paper cites Revisiting weak-to-strong consistency in semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Revisiting weak-to-strong consistency in semi-supervised semantic segmentation

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.766748Z

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Observation 6c8129a1-6eec-42df-a52d-010e3fd26a26 · outbound

This paper cites k-means mask transformer.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation k-means mask transformer

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.736360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 81e52982-34e8-42c8-8c53-2f8a7a9e7e05 · outbound

This paper cites Convolutions die hard: Open-vocabulary seg- mentation with single frozen convolutional clip.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Convolutions die hard: Open-vocabulary seg- mentation with single frozen convolutional clip

Reference 76

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Observation 12b62cc0-210d-46b8-ad62-ef6a816f2b50 · outbound

This paper cites A simple baseline for semi-supervised semantic seg- mentation with strong data augmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation A simple baseline for semi-supervised semantic seg- mentation with strong data augmentation

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.706427Z

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Observation 588512ee-6f86-4415-92e6-0a5876921592 · outbound

This paper cites Cutmix: Regu- larization strategy to train strong classifiers with localizable features.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Cutmix: Regu- larization strategy to train strong classifiers with localizable features

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.687682Z

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Observation 09492a4b-6ba2-4675-9919-71e7103319ba · outbound

This paper cites Unifying panop- tic segmentation for autonomous driving.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Unifying panop- tic segmentation for autonomous driving

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.669174Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 51909f66-e1d8-4579-b572-79f9f23bb0ab · outbound

This paper cites Sigmoid loss for language image pre-training.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Sigmoid loss for language image pre-training

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.651732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e4e9821e-a648-4292-8fcb-1c88aebe8f5c · outbound

This paper cites Pixel contrastive-consistent semi-supervised semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Pixel contrastive-consistent semi-supervised semantic segmentation

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.630546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a21c1537-c52d-409a-b6c2-ba73043e3c9f · outbound

This paper cites Scene parsing through ade20k dataset.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Scene parsing through ade20k dataset

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T17:44:34.499005Z

Source-reported events for the cited work

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Observation a47a27f7-0d70-4f68-a832-c49d770e1769 · outbound

This paper cites Extract free dense labels from clip.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Extract free dense labels from clip

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.600024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 66002f5a-9e03-4bc2-9cbc-3fa6068ab5cd · outbound

This paper cites Pseudoseg: Designing pseudo labels for semantic segmentation.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Pseudoseg: Designing pseudo labels for semantic segmentation

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:44:34.582565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dbc5f780-44d7-47ed-8900-ca1e3d3662b0 · outbound

This paper cites Lars: A diverse panoptic maritime obstacle detection dataset and benchmark.

DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation Lars: A diverse panoptic maritime obstacle detection dataset and benchmark

Reference 85

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T17:44:34.563582Z

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