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Image Segmentation

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하위 태스크: 1
평가표: 13
보존된 평가 기록: 34

Image Segmentation is a computer vision task that involves dividing an image into multiple segments or regions, each of which corresponds to a different object or part of an object. The goal of image segmentation is to assign a unique label or category to each pixel in the image, so that pixels with similar attributes are grouped together.

코드

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

https://github.com/biolins/insideness_data

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Do Neural Networks for Segmentation Understand Insideness?

https://github.com/biomedia-mbzuai/brats2024_biomediambz

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On Enhancing Brain Tumor Segmentation Across Diverse Populations with Convolutional Neural Networks

https://github.com/biomedia-mbzuai/contrastive-echo

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Contrastive Pretraining for Echocardiography Segmentation with Limited Data

https://github.com/biomedia-mbzuai/salt

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SALT: Singular Value Adaptation with Low-Rank Transformation

https://github.com/biomedia-mira/masf

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Domain Generalization via Model-Agnostic Learning of Semantic Features

https://github.com/biomedia-mira/stochastic_segmentation_networks

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Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty

https://github.com/biomedia-repo/pg-fanet

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Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation

https://github.com/biswassanket/docsegtr

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DocSegTr: An Instance-Level End-to-End Document Image Segmentation Transformer

https://github.com/blaschko/supermodularLP

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Slack and Margin Rescaling as Convex Extensions of Supermodular Functions

https://github.com/bluecdm/Long-tailed-recognition

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Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels

https://github.com/bluehenglee/mli-msc

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Weakly Supervised Segmentation Framework for Thyroid Nodule Based on High-confidence Labels and High-rationality Losses

https://github.com/bobrown/ccda_lgfa

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Curriculum-style Local-to-global Adaptation for Cross-domain Remote Sensing Image Segmentation

https://github.com/boqian333/e2enet-medical

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E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation

https://github.com/bosonphoton/abstractedgaussianprototypes

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Abstracted Gaussian Prototypes for One-Shot Concept Learning

https://github.com/bowang-lab/medsam

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Segment Anything in Medical Images

https://github.com/bowenc0221/boundary-iou-api

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Boundary IoU: Improving Object-Centric Image Segmentation Evaluation

https://github.com/brack-wang/zeco

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ZECO: ZeroFusion Guided 3D MRI Conditional Generation

https://github.com/brainimageanalysis/ici-loss

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Improving Segmentation of Objects with Varying Sizes in Biomedical Images using Instance-wise and Center-of-Instance Segmentation Loss Function

https://github.com/brian-h-wang/LDLS

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LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images

https://github.com/briley-byl123/mper

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Multi-Prototype Embedding Refinement for Semi-Supervised Medical Image Segmentation

https://github.com/bscs12/bussam

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Ultrasound SAM Adapter: Adapting SAM for Breast Lesion Segmentation in Ultrasound Images

https://github.com/bupt-ai-cz/wuda

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WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain Labels

https://github.com/bwgzk/cyclemix

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CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision

https://github.com/bwittmann/vesselFM

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vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation

https://github.com/bx0903/pdc

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Parameter Decoupling Strategy for Semi-supervised 3D Left Atrium Segmentation

https://github.com/by-liu/confkd

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Segmentation with mixed supervision: Confidence maximization helps knowledge distillation

https://github.com/c-a-schiller/var4arl

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Virtual Augmented Reality for Atari Reinforcement Learning

https://github.com/cai4cai/ace-dliris

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Average Calibration Error: A Differentiable Loss for Improved Reliability in Image Segmentation

https://github.com/caipengzhou/brau-netplusplus

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BRAU-Net++: U-Shaped Hybrid CNN-Transformer Network for Medical Image Segmentation

https://github.com/caoluyang0830/cvbm

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Background Matters: A Cross-view Bidirectional Modeling Framework for Semi-supervised Medical Image Segmentation

https://github.com/caoql98/frinet

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Few-Shot Rotation-Invariant Aerial Image Semantic Segmentation

https://github.com/carrenD/ummkd

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Unpaired Multi-modal Segmentation via Knowledge Distillation

https://github.com/casia-iva-lab/fastsam

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Fast Segment Anything

https://github.com/catherine-r-he/hetnet

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Efficient Mirror Detection via Multi-level Heterogeneous Learning

https://github.com/cccccczh404/h-sam

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Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding

https://github.com/cchen-cc/Robust-Mseg

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Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion

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