Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation | Paper Citation Record

Observation 4da9ba6b-1ccd-44fd-99a5-86af563dffd4 · outbound

This paper cites Few-shot seg- mentation without meta-learning: A good transductive infer- ence is all you need? InCVPR, 2021.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Few-shot seg- mentation without meta-learning: A good transductive infer- ence is all you need? InCVPR, 2021

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Observation 63bfca29-0146-43a0-aa74-74c8a032d9a7 · outbound

This paper cites Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration.TMI, 2013.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration.TMI, 2013

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Observation 569efcb9-e421-499c-b0a3-d682e9468e34 · outbound

This paper cites Pixel matching network for cross-domain few- shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Pixel matching network for cross-domain few- shot segmentation

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Observation 18ee7e8e-c06e-4515-8ead-c410723676d0 · outbound

This paper cites Cross-domain few-shot semantic segmentation via doubly matching transformation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Cross-domain few-shot semantic segmentation via doubly matching transformation

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Observation 6a2bb31e-ff91-408d-aec4-0fd13e3495ce · outbound

This paper cites A closer look at few-shot classi- fication.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation A closer look at few-shot classi- fication

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Observation 33bbed9f-03ca-40b6-a965-d88e14c3c804 · outbound

This paper cites Holistic pro- totype activation for few-shot segmentation.TPAMI, 2022.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Holistic pro- totype activation for few-shot segmentation.TPAMI, 2022

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Observation 3c321538-2924-4369-a1fe-69183c1dc9ca · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

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Observation fb779170-c30d-43dd-96dc-8dfdcc201022 · outbound

This paper cites Deepglobe 2018: A challenge to parse the earth through satellite images.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Deepglobe 2018: A challenge to parse the earth through satellite images

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Observation 06ef6f77-a9d4-4d18-be66-40355c78cbae · outbound

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

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Imagenet: A large-scale hierarchical image database

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Observation d8093f6e-56df-4dc1-9422-1c81f90442bb · outbound

This paper cites Few-shot semantic segmen- tation with prototype learning.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Few-shot semantic segmen- tation with prototype learning

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Observation 3853d164-c775-40e9-8978-6ed3fe03a21a · outbound

This paper cites The pascal visual object classes (voc) challenge.IJCV, 2010.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation The pascal visual object classes (voc) challenge.IJCV, 2010

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Observation 18ad9deb-59e3-4c70-a64c-99cb4795a9de · outbound

This paper cites DARNet: Bridging Domain Gaps in Cross-Domain Few-Shot Segmentation with Dynamic Adaptation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation DARNet: Bridging Domain Gaps in Cross-Domain Few-Shot Segmentation with Dynamic Adaptation

Reference 12

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Observation 068715f3-0e7b-403d-a876-1b10da9f570a · outbound

This paper cites Self- support few-shot semantic segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Self- support few-shot semantic segmentation

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Observation 4e794a14-7653-496a-b0ee-e422bd9bc4ec · outbound

This paper cites Adapt- ing in-domain few-shot segmentation to new domains with- out retraining.arXiv preprint arXiv:2504.21414, 2025.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Adapt- ing in-domain few-shot segmentation to new domains with- out retraining.arXiv preprint arXiv:2504.21414, 2025

Reference 14

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Observation 38524a05-8c23-469f-a425-94239054d674 · outbound

This paper cites Cross-domain few-shot object detection via enhanced open-set object detector.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Cross-domain few-shot object detection via enhanced open-set object detector

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Observation 8d763a94-1c1e-4737-a45b-8ca4503afc6c · outbound

This paper cites Acrofod: An adaptive method for cross-domain few-shot object detection.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Acrofod: An adaptive method for cross-domain few-shot object detection

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Observation 38a9e6b3-11d2-40c2-8ebf-32dba059d080 · outbound

This paper cites Simple copy-paste is a strong data augmentation method for instance segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Simple copy-paste is a strong data augmentation method for instance segmentation

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Observation b59bf0b8-a630-45c8-a49c-a892e26df37f · outbound

This paper cites Deep residual learning for image recognition.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Deep residual learning for image recognition

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Observation 2467e82b-46e2-46d6-986e-e3597069b973 · outbound

This paper cites Apseg: Auto-prompt network for cross-domain few-shot semantic segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Apseg: Auto-prompt network for cross-domain few-shot semantic segmentation

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Observation f73fc0a1-8a49-4456-b61f-ddb3692908be · outbound

This paper cites Adapt before comparison: A new perspective on cross-domain few-shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Adapt before comparison: A new perspective on cross-domain few-shot segmentation

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Observation 89333235-e389-4169-9e89-4ede0511b05c · outbound

This paper cites Cross attention network for few-shot classi- fication.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Cross attention network for few-shot classi- fication

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Observation d8f522f9-750d-4c37-8a3e-14a6dd80222d · outbound

This paper cites Restnet: Boosting cross-domain few-shot segmentation with residual transformation network.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Restnet: Boosting cross-domain few-shot segmentation with residual transformation network

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Observation 684ac5ec-9301-4ecc-bc49-4ff32b1743db · outbound

This paper cites Semantic segmentation of underwater im- agery: Dataset and benchmark.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Semantic segmentation of underwater im- agery: Dataset and benchmark

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Observation 065fb348-27c6-4996-bf59-9cca9217d1f2 · outbound

This paper cites Automatic tuberculosis screening using chest radio- graphs.TMI, 2013.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Automatic tuberculosis screening using chest radio- graphs.TMI, 2013

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Observation 38f0a9ab-fda9-4e96-9e74-9e0c16447ca6 · outbound

This paper cites Few-shot object detection via feature reweighting.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Few-shot object detection via feature reweighting

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Observation d417a86a-d44f-4f70-acbe-9c92594007dd · outbound

This paper cites Relational embedding for few-shot classification.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Relational embedding for few-shot classification

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Observation a575693e-8b83-4385-b56c-58178c7e35a3 · outbound

This paper cites Segment any- thing.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Segment any- thing

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Observation 7bcdb409-26e4-4f38-96e4-8904649e2161 · outbound

This paper cites Learning what not to segment: A new perspective on few- shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Learning what not to segment: A new perspective on few- shot segmentation

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This paper cites Base and meta: A new perspective on few-shot segmentation.TPAMI, 2023.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Base and meta: A new perspective on few-shot segmentation.TPAMI, 2023

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Observation dd018d19-e8ee-41fa-87bc-0d57ae7abca2 · outbound

This paper cites Cross-domain few-shot se- mantic segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Cross-domain few-shot se- mantic segmentation

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Observation ba57faaf-0614-45b1-a737-dec034792610 · outbound

This paper cites Adaptive prototype learning and allocation for few-shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Adaptive prototype learning and allocation for few-shot segmentation

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Observation 20a58838-53d0-47ae-a71a-824789368824 · outbound

This paper cites Fss-1000: A 1000-class dataset for few- shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Fss-1000: A 1000-class dataset for few- shot segmentation

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Observation 9ac1c39e-3c40-4bf6-983a-ae05e60756b0 · outbound

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Constructing self-motivated pyramid curriculums for cross- domain semantic segmentation: A non-adversarial approach

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Inter- mediate prototype mining transformer for few-shot semantic segmentation

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Simpler is better: Few-shot semantic segmenta- tion with classifier weight transformer

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Pfenet++: Boosting few-shot semantic segmentation with the noise-filtered context-aware prior mask.TPAMI, 2023

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Hypercorrela- tion squeeze for few-shot segmentation

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Automatic differentiation in pytorch

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Guided curriculum model adaptation and uncertainty-aware evalua- tion for semantic nighttime image segmentation

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation

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Observation 231b2e0f-8a03-4f24-8180-f7235d73abc6 · outbound

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Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation The ham10000 dataset, a large collection of multi-source der- matoscopic images of common pigmented skin lesions.Sci- entific Data, 2018

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Observation 2f6714f3-f04b-45c1-b377-e643be471fb3 · outbound

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Observation b29ff388-15d4-453e-95f8-d6b61048793a · outbound

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Observation 1c00ee52-0147-4dde-91bb-25431f2a2352 · outbound

This paper cites Few-shot object detection and viewpoint estimation for objects in the wild.TPAMI, 2022.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Few-shot object detection and viewpoint estimation for objects in the wild.TPAMI, 2022

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:26.440717Z

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Observation eef7e07d-559d-4fc6-b81b-fe88d80b9897 · outbound

This paper cites Self-calibrated cross attention network for few-shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Self-calibrated cross attention network for few-shot segmentation

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:26.576312Z

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Observation 84750dc9-802f-455b-b874-7ade1b3b08a3 · outbound

This paper cites Eliminating feature ambi- guity for few-shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Eliminating feature ambi- guity for few-shot segmentation

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:26.719054Z

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Observation 5dd83b9c-0f83-42e8-9af5-abd65874736e · outbound

This paper cites Hybrid mamba for few-shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Hybrid mamba for few-shot segmentation

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:26.859599Z

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Observation 0a6356af-4909-46c9-b5b9-b11e2ab58d6d · outbound

This paper cites Prototype mixture models for few-shot semantic seg- mentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Prototype mixture models for few-shot semantic seg- mentation

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:26.992882Z

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Observation 799dc44b-8d82-41c0-90b9-df4012f80d1c · outbound

This paper cites TAVP: Task-Adaptive Visual Prompt for Cross-domain Few-shot Segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation TAVP: Task-Adaptive Visual Prompt for Cross-domain Few-shot Segmentation

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:27.137388Z

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Observation f04c8f28-a8a6-4559-9ea8-5af81a6961e3 · outbound

This paper cites Mi- anet: Aggregating unbiased instance and general information for few-shot semantic segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Mi- anet: Aggregating unbiased instance and general information for few-shot semantic segmentation

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:27.259426Z

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Observation b1a2aaf8-452d-4211-a72a-bdde494a6fa8 · outbound

This paper cites Self-guided and cross-guided learning for few-shot segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Self-guided and cross-guided learning for few-shot segmentation

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:27.421280Z

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Observation 91525dfc-ff02-4362-943d-f7aae7647c6f · outbound

This paper cites Pyramid graph networks with connection attentions for region-based one-shot semantic segmentation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Pyramid graph networks with connection attentions for region-based one-shot semantic segmentation

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:27.522866Z

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Observation f3c9bcb1-0d32-44d2-bbd6-603d5c89f458 · outbound

This paper cites Canet: Class-agnostic segmentation networks with it- erative refinement and attentive few-shot learning.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Canet: Class-agnostic segmentation networks with it- erative refinement and attentive few-shot learning

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:27.649657Z

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Observation 78b421c5-290c-4611-85f4-a9a004d8366b · outbound

This paper cites Few-shot segmentation via cycle-consistent trans- former.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Few-shot segmentation via cycle-consistent trans- former

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:27.875444Z

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Observation ec3ce1cd-8907-4fff-9df4-92702d91a5c2 · outbound

This paper cites Meta-detr: Image-level few-shot detection with inter-class correlation exploitation.TPAMI, 2022.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Meta-detr: Image-level few-shot detection with inter-class correlation exploitation.TPAMI, 2022

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:28.055602Z

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Observation 5f2d4518-9058-4499-bce9-ec739d6380f5 · outbound

This paper cites Personalize segment anything model with one shot.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Personalize segment anything model with one shot

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:28.320344Z

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Observation a2010f3b-c570-44c6-a3fc-8a689ace45a1 · outbound

This paper cites A curriculum domain adaptation approach to the se- mantic segmentation of urban scenes.TPAMI, 2019.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation A curriculum domain adaptation approach to the se- mantic segmentation of urban scenes.TPAMI, 2019

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:28.521654Z

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Observation a656123f-ab1e-4117-90ed-147bcb5c6aa6 · outbound

This paper cites Addressing background context bias in few-shot segmentation through iterative modulation.

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation Addressing background context bias in few-shot segmentation through iterative modulation

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:28.681011Z

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