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Weakly supervised segmentation

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/liuweide01/Cross-Image-Region-Mining-with-Region-Prototypical-Network-for-Weakly-Supervised-Segmentation

공식 코드

Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation

https://github.com/llmir/fedicra

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Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregation

https://github.com/lwhyc/oneshot_weaklyseg

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One-shot Weakly-Supervised Segmentation in Medical Images

https://github.com/lyxdlii/procns

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ProCNS: Progressive Prototype Calibration and Noise Suppression for Weakly-Supervised Medical Image Segmentation

https://github.com/neouyghur/sess

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SESS: Saliency Enhancing with Scaling and Sliding

https://github.com/nyukat/GLAM

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Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis

https://github.com/olivesgatech/scribe-robustness-overfit

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Robustness and Overfitting Behavior of Implicit Background Models

https://github.com/pathak22/ccnn

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Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

https://github.com/rockNroll87q/CER3BRUM

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CEREBRUM: a fast and fully-volumetric Convolutional Encoder-decodeR for weakly-supervised sEgmentation of BRain strUctures from out-of-the-scanner MRI

https://github.com/s-sd/spurl

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Competing for pixels: a self-play algorithm for weakly-supervised segmentation

https://github.com/sbelharbi/deep-wsl-histo-min-max-uncertainty

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Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty

https://github.com/seanxuu/PWISeg

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PWISeg: Point-based Weakly-supervised Instance Segmentation for Surgical Instruments

https://github.com/serenos/lwsis

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LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving

https://github.com/shimoda-uec/ssdd

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Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation

https://github.com/soumickmj/GPModels

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Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification

https://github.com/svrtk/masc-multi-task-segmentation-and-classification

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Multi-task learning for joint weakly-supervised segmentation and aortic arch anomaly classification in fetal cardiac MRI

https://github.com/talshaharabany/what-is-where-by-looking

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What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text Inputs

https://github.com/tldr-group/HR-Dv2

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Upsampling DINOv2 features for unsupervised vision tasks and weakly supervised materials segmentation

https://github.com/twke18/SPML

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Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning

https://github.com/ucuapps/WSMIS

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Weakly-Supervised Segmentation for Disease Localization in Chest X-Ray Images

https://github.com/wbkit/scribbles4all

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Scribbles for All: Benchmarking Scribble Supervised Segmentation Across Datasets

https://github.com/windstormer/ame-cam

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AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain Tumor

https://github.com/winterpan2017/proto2seg

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Human-machine Interactive Tissue Prototype Learning for Label-efficient Histopathology Image Segmentation

https://github.com/xulianuwa/AuxSegNet

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Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation

https://github.com/zengxianyu/jsws

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Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation

https://github.com/zhangye-zoe/dawn

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DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task Interactions

https://github.com/zhaoyangwei123/sapnet

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Semantic-aware SAM for Point-Prompted Instance Segmentation

https://github.com/2023-MindSpore-1/ms-code-213/tree/main/essay-recogination

OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold

https://github.com/Ahmadreza-Jeddi/rloss

Constrained-CNN losses for weakly supervised segmentation

https://github.com/HiLab-git/WSL4MIS

WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image

https://github.com/HuseyinAfser/A-Baseline-Statistical-Method-For-Robust-User-Assisted-Multiple-Segmentation

A Baseline Statistical Method For Robust User-Assisted Multiple Segmentation

https://github.com/LIVIAETS/boxes_tightness_prior

Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision

https://github.com/MindSpore-MS-Code2/code0/tree/main/essay-recogination

OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold

https://github.com/MindSpore-paper-code-3/code7/tree/main/essay-recogination

OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold

https://github.com/MindSpore-paper-code-3/code8/tree/main/essay-recogination

OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold

https://github.com/PengyiZhang/MIADeepSSL

Constrained-CNN losses for weakly supervised segmentation

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