Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation | Paper Citation Record

Observation 090ca234-56dd-44bb-9fbb-8c4ed0a49cd8 · outbound

This paper cites Label-embedding for image classification.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Label-embedding for image classification

Reference 1

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This paper cites Evaluation of output embeddings for fine-grained image classification.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Evaluation of output embeddings for fine-grained image classification

Reference 2

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This paper cites Paco: a novel procrustes application to co- phylogenetic analysis.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Paco: a novel procrustes application to co- phylogenetic analysis

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This paper cites Zero-shot semantic segmentation.Advances in Neural Information Processing Systems, 32, 2019.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Zero-shot semantic segmentation.Advances in Neural Information Processing Systems, 32, 2019

Reference 4

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This paper cites Emerg- ing properties in self-supervised vision transformers.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Emerg- ing properties in self-supervised vision transformers

Reference 5

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Observation e5294c37-e609-4e46-8a3c-cf8095d8f3e0 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 6

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This paper cites CostFormer:Cost Transformer for Cost Aggregation in Multi-view Stereo.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation CostFormer:Cost Transformer for Cost Aggregation in Multi-view Stereo

Reference 7

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This paper cites Detect what you can: Detecting and representing objects using holistic mod- els and body parts.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Detect what you can: Detecting and representing objects using holistic mod- els and body parts

Reference 8

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Observation 960bfbdc-2388-4ebf-b73c-ae8aff1459b1 · outbound

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Per- pixel classification is not all you need for semantic segmen- tation

Reference 9

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Observation 017410d7-a138-4a38-a0e6-e682bb6ec7a4 · outbound

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Masked-attention mask transformer for universal image segmentation

Reference 10

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Observation 3c8c3fda-25fd-4659-92ca-def64e05f723 · outbound

This paper cites Cats: Cost aggre- gation transformers for visual correspondence.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Cats: Cost aggre- gation transformers for visual correspondence

Reference 11

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Observation 42b2915f-ac15-49a0-b8f1-90eabb1b2121 · outbound

This paper cites Cats++: Boosting cost aggregation with convolutions and transformers.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Cats++: Boosting cost aggregation with convolutions and transformers

Reference 12

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Observation 258a8713-8db5-4b25-a073-76d7ab53602c · outbound

This paper cites CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation

Reference 13

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This paper cites Understanding Multi-Granularity for Open-Vocabulary Part Segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Understanding Multi-Granularity for Open-Vocabulary Part Segmentation

Reference 14

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Observation c80a8c29-2b16-4309-95c7-f85850fd7924 · outbound

This paper cites Unsupervised part discovery from con- trastive reconstruction.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Unsupervised part discovery from con- trastive reconstruction

Reference 15

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Observation a2df2f78-3101-438a-815d-8fc89ea04d1a · outbound

This paper cites Histograms of oriented gra- dients for human detection.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Histograms of oriented gra- dients for human detection

Reference 16

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Imagenet: A large-scale hierarchical image database

Reference 17

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Observation 2c478850-7782-4a0c-b1d1-dc5066260f8b · outbound

This paper cites Open-Vocabulary Universal Image Segmentation with MaskCLIP.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Open-Vocabulary Universal Image Segmentation with MaskCLIP

Reference 18

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Observation 4dc9a23b-7481-4ac6-af53-ceb46f007112 · outbound

This paper cites Generalized jensen- shannon divergence loss for learning with noisy labels.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Generalized jensen- shannon divergence loss for learning with noisy labels

Reference 19

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Observation 06cadc3c-d79f-4da8-a2ef-29f2059df66a · outbound

This paper cites De- vise: A deep visual-semantic embedding model.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation De- vise: A deep visual-semantic embedding model

Reference 20

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Observation fc469418-4c88-4de4-987b-31bace6db67c · outbound

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Scal- ing open-vocabulary image segmentation with image-level labels

Reference 21

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Observation 6235dc49-b571-43c3-a57b-ae6e211aa201 · outbound

This paper cites Open-vocabulary Object Detection via Vision and Language Knowledge Distillation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Open-vocabulary Object Detection via Vision and Language Knowledge Distillation

Reference 22

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This paper cites Aˆ 3: Accelerating attention mechanisms in neural networks with approximation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Aˆ 3: Accelerating attention mechanisms in neural networks with approximation

Reference 23

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This paper cites Global knowledge calibration for fast open-vocabulary segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Global knowledge calibration for fast open-vocabulary segmentation

Reference 24

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Observation a27ce1e4-aef7-4885-b14d-15ea7e063f22 · outbound

This paper cites Partimagenet: A large, high- quality dataset of parts.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Partimagenet: A large, high- quality dataset of parts

Reference 25

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Observation 36c60660-742d-46e9-a6cc-d3ca80b2c58b · outbound

This paper cites Compositor: Bottom-up clustering and compositing for robust part and object segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Compositor: Bottom-up clustering and compositing for robust part and object segmentation

Reference 26

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Observation 70df0c52-92af-403e-863d-ad6011ba1586 · outbound

This paper cites Deep residual learning for image recognition.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Deep residual learning for image recognition

Reference 27

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This paper cites Mask r-cnn.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Mask r-cnn

Reference 28

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Observation 7daf053a-b5a3-4517-8205-b2b6b1338d37 · outbound

This paper cites Cost aggregation with 4d convolutional swin transformer for few-shot segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Cost aggregation with 4d convolutional swin transformer for few-shot segmentation

Reference 29

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This paper cites Unifying feature and cost aggregation with transformers for semantic and visual correspondence.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Unifying feature and cost aggregation with transformers for semantic and visual correspondence

Reference 30

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Observation f83b5638-299d-49c2-a4a6-d65f736e96ca · outbound

This paper cites Fast cost-volume filtering for visual correspondence and beyond.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Fast cost-volume filtering for visual correspondence and beyond

Reference 31

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This paper cites Scops: Self-supervised co-part segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Scops: Self-supervised co-part segmentation

Reference 32

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 33

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This paper cites Salad: Part-level latent diffusion for 3d shape gen- eration and manipulation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Salad: Part-level latent diffusion for 3d shape gen- eration and manipulation

Reference 34

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This paper cites Language-driven Semantic Segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Language-driven Semantic Segmentation

Reference 35

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Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Mask dino: Towards a unified transformer-based framework for object detection and segmentation

Reference 36

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Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 37

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This paper cites PartGLEE: A Foundation Model for Recognizing and Parsing Any Objects.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation PartGLEE: A Foundation Model for Recognizing and Parsing Any Objects

Reference 38

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This paper cites A Closer Look at the Explainability of Contrastive Language-Image Pre-training.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation A Closer Look at the Explainability of Contrastive Language-Image Pre-training

Reference 39

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Open-vocabulary semantic segmentation with mask-adapted clip

Reference 40

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Observation 211d525b-f2e8-46a8-9a14-e31c3955d583 · outbound

This paper cites Divergence measures based on the shannon en- tropy.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Divergence measures based on the shannon en- tropy

Reference 41

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Observation 3fdcd5fb-6d99-41d8-8102-35d80a7dd0ed · outbound

This paper cites Editgan: High-precision semantic image editing.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Editgan: High-precision semantic image editing

Reference 42

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Observation 43330f00-7824-4ae3-80a7-b36bf3d4c7fa · outbound

This paper cites Sift flow: Dense correspondence across scenes and its applications.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Sift flow: Dense correspondence across scenes and its applications

Reference 43

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Observation ed449e01-2df5-4761-b57c-dbbc53ed5424 · outbound

This paper cites Se- mantic correspondence as an optimal transport problem.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Se- mantic correspondence as an optimal transport problem

Reference 44

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Observation 202b5526-63d1-4c6e-8ce2-e1a74fc9d079 · outbound

This paper cites Open-Vocabulary Segmentation with Semantic-Assisted Calibration.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Open-Vocabulary Segmentation with Semantic-Assisted Calibration

Reference 45

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Observation 611ca277-4f8d-436c-a108-cde8ad692068 · outbound

This paper cites 3d part guided image editing for fine-grained object understanding.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation 3d part guided image editing for fine-grained object understanding

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:38.295859Z

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Observation 86fd6094-08d6-4e51-943d-c608a4f07b0c · outbound

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Swin transformer: Hierarchical vision transformer using shifted windows

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:38.277161Z

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Observation 7f0f0b9c-914f-44b0-92ac-9df8af4805c5 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Fully convolutional networks for semantic segmentation

Reference 48

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Observation 66bdb88f-8352-4ee8-a5aa-949b25c137ce · outbound

This paper cites Decoupled Weight Decay Regularization.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Decoupled Weight Decay Regularization

Reference 49

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Source-reported events for the cited work

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Observation f19caff0-bc32-4b04-a66a-11d598250310 · outbound

This paper cites Image segmenta- tion using text and image prompts.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Image segmenta- tion using text and image prompts

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:38.051535Z

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Observation 619768ee-e4cb-4441-a17f-6cdbaa304d53 · outbound

This paper cites Wordnet: a lexical database for english.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Wordnet: a lexical database for english

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:38.036443Z

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Observation 7e2e7a7b-f640-4ab1-a2b8-119db16410c2 · outbound

This paper cites Hyperpixel flow: Semantic correspondence with multi-layer neural features.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Hyperpixel flow: Semantic correspondence with multi-layer neural features

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:38.019994Z

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Observation 80e081cf-dc03-4f6f-bbbe-9f18dc69bb87 · outbound

This paper cites Learning to compose hypercolumns for visual correspon- dence.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Learning to compose hypercolumns for visual correspon- dence

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.992362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0e219efb-c350-4ad7-bafa-d0f6cdb3e00d · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation DINOv2: Learning Robust Visual Features without Supervision

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.305078Z

Source-reported events for the cited work

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Observation 8b02dd13-5452-43aa-b523-22bd10a27920 · outbound

This paper cites To- wards open-world segmentation of parts.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation To- wards open-world segmentation of parts

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.952351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a1d534f8-1caf-4686-b0c4-6bda92071e15 · outbound

This paper cites Computational optimal transport: With applications to data science.Foundations and Trends® in Machine Learning, 11(5-6):355–607, 2019.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Computational optimal transport: With applications to data science.Foundations and Trends® in Machine Learning, 11(5-6):355–607, 2019

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.862486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b6521947-2918-498f-92ae-d0dbaac1feb9 · outbound

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Learning transferable visual models from natural language supervi- sion

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.711139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6d18e1a8-32d5-4ff2-a73b-61630d19d78e · outbound

This paper cites Neighbourhood con- sensus networks.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Neighbourhood con- sensus networks

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.695243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6e7561bd-6317-4b1a-a42c-ee91e747402c · outbound

This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation U- net: Convolutional networks for biomedical image segmen- tation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.475790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59452721-16ab-4ab2-aeab-4973fa80a5ce · outbound

This paper cites Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.521113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caaf3bd3-3989-44d0-a44b-fdc2a81be1ff · outbound

This paper cites Going denser with open-vocabulary part segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Going denser with open-vocabulary part segmentation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.603310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8f782bcd-1d60-44cd-8084-b5685af8d568 · outbound

This paper cites Parts and wholes in face recognition.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Parts and wholes in face recognition

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.407465Z

Source-reported events for the cited work

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Observation 4a98ab58-959a-4065-a6e0-c904a9e51181 · outbound

This paper cites Glu- net: Global-local universal network for dense flow and corre- spondences.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Glu- net: Global-local universal network for dense flow and corre- spondences

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.585172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cbf97a8-48c1-45a1-a3f1-739676d60de5 · outbound

This paper cites Pdisconet: Semantically consistent part discovery for fine-grained recognition.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Pdisconet: Semantically consistent part discovery for fine-grained recognition

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.643066Z

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Observation 3725fade-665e-4dcf-b2d1-5b39d852d46c · outbound

This paper cites Attention is all you need.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Attention is all you need

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.670739Z

Source-reported events for the cited work

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Observation 8ad3e1a2-f5b4-4b3d-9645-349a71d6a855 · outbound

This paper cites Optimal transport: old and new.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Optimal transport: old and new

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.294110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 42bf180c-584e-4349-bb11-b2689d7bbf2b · outbound

This paper cites In- structpart: Affordance-based part segmentation from lan- guage instruction.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation In- structpart: Affordance-based part segmentation from lan- guage instruction

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.278144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation baeead81-f078-4bc4-9c31-1eb858c9192e · outbound

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Pyramid vision transformer: A versatile backbone for dense prediction without convolutions

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.259446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 356ad15a-7c21-48c1-90f3-fc090b51284f · outbound

This paper cites InstanceDiffusion: Instance-level Control for Image Generation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation InstanceDiffusion: Instance-level Control for Image Generation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.687564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c0411f4-e0f9-42f2-b1ac-38381ad30507 · outbound

This paper cites Ov-parts: Towards open- vocabulary part segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Ov-parts: Towards open- vocabulary part segmentation

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.227174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation da2551fc-7433-4889-bcd0-23e02b1e673b · outbound

This paper cites Semantic projection network for zero-and few-label semantic segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Semantic projection network for zero-and few-label semantic segmentation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:37.076600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 73d0a2c2-defd-4361-8643-d1ab7e9d7ffb · outbound

This paper cites SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.818590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e494ba32-11ca-430c-b152-c5ecf18e8f89 · outbound

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

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Open-vocabulary panop- tic segmentation with text-to-image diffusion models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.892353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ad2a31a-3111-4423-a6d7-84bc4f46a561 · outbound

This paper cites A simple baseline for open- vocabulary semantic segmentation with pre-trained vision- 11 language model.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation A simple baseline for open- vocabulary semantic segmentation with pre-trained vision- 11 language model

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:36.899779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 02c90f8f-228b-48c9-ac0e-3cf840ace960 · outbound

This paper cites HomeRobot: Open-Vocabulary Mobile Manipulation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation HomeRobot: Open-Vocabulary Mobile Manipulation

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:35.950172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f091fff-f0d5-4d06-8878-ec5c753b7a37 · outbound

This paper cites C2fnas: Coarse- to-fine neural architecture search for 3d medical image seg- mentation.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation C2fnas: Coarse- to-fine neural architecture search for 3d medical image seg- mentation

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:36.882710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bd5c994d-3bb6-4156-83c4-f5307238b284 · outbound

This paper cites Convolutions die hard: Open-vocabulary seg- mentation with single frozen convolutional clip.Advances in Neural Information Processing Systems, 36, 2024.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Convolutions die hard: Open-vocabulary seg- mentation with single frozen convolutional clip.Advances in Neural Information Processing Systems, 36, 2024

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:36.866331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bfdf972c-adc4-4cb7-9833-a38f74b2cb8c · outbound

This paper cites Open-vocabulary object detection using captions.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Open-vocabulary object detection using captions

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:36.824494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d9dca9e4-dc36-410a-acb5-14709fc7a54f · outbound

This paper cites Open vocabulary scene parsing.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Open vocabulary scene parsing

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:36.729546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation af7668bc-2420-4675-ac2a-d7ae68aca7a6 · outbound

This paper cites Scene parsing through ade20k dataset.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Scene parsing through ade20k dataset

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:36.003829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77201593-316d-4da1-b232-5debc540a1b0 · outbound

This paper cites Extract free dense labels from clip.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Extract free dense labels from clip

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:36.632220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b5d453f8-a3e4-410f-81a9-fa32156e1a75 · outbound

This paper cites Learning to prompt for vision-language models.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation Learning to prompt for vision-language models

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-10T19:48:36.012707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 788bf27f-901c-49ce-9303-eb0147d25a54 · outbound

This paper cites person” (b) “person’s eye.

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation person” (b) “person’s eye

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:48:36.543756Z

Source-reported events for the cited work

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