Papers with Code 아카이브

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/itmo-mmrm-lab/cellpose

공식 코드

Cellpose+, a morphological analysis tool for feature extraction of stained cell images

https://github.com/itruonghai/segtransvae

공식 코드

SegTransVAE: Hybrid CNN -- Transformer with Regularization for medical image segmentation

https://github.com/ivandrokin/torch-conv-kan

공식 코드

Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies

https://github.com/ivezakis/effisegnet

공식 코드

EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder

https://github.com/iweisskohl/deep-evidential-fusion

공식 코드

Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation

https://github.com/iweisskohl/evidence-fusion-with-contextual-discounting

공식 코드

Evidence fusion with contextual discounting for multi-modality medical image segmentation

https://github.com/j-morano/multimodal-ssl-fpn

공식 코드

Self-supervised learning via inter-modal reconstruction and feature projection networks for label-efficient 3D-to-2D segmentation

https://github.com/jacobzhaoziyuan/ACT-Net

공식 코드

ACT-Net: Asymmetric Co-Teacher Network for Semi-supervised Memory-efficient Medical Image Segmentation

https://github.com/jacobzhaoziyuan/DSAL

공식 코드

DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation

https://github.com/jacobzhaoziyuan/MMGL

공식 코드

MMGL: Multi-Scale Multi-View Global-Local Contrastive learning for Semi-supervised Cardiac Image Segmentation

https://github.com/jacobzhaoziyuan/MT-UDA

공식 코드

MT-UDA: Towards Unsupervised Cross-modality Medical Image Segmentation with Limited Source Labels

https://github.com/jacobzhaoziyuan/SAAL

공식 코드

Self-supervised Assisted Active Learning for Skin Lesion Segmentation

https://github.com/jacobzhaoziyuan/le-uda

공식 코드

LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation

https://github.com/jamesjg/foodsam

공식 코드

FoodSAM: Any Food Segmentation

https://github.com/janelia-cellmap/dacapo

공식 코드

DaCapo: a modular deep learning framework for scalable 3D image segmentation

https://github.com/janelia-flyem/DVIDSparkServices

공식 코드

Large-Scale Electron Microscopy Image Segmentation in Spark

https://github.com/jankowskichristopher/red-teaming-segment-anything-model

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Red-Teaming Segment Anything Model

https://github.com/jannctu/TIN

공식 코드

Traditional Method Inspired Deep Neural Network for Edge Detection

https://github.com/jayparanjape/blackbox

공식 코드

Blackbox Adaptation for Medical Image Segmentation

https://github.com/jayparanjape/svdsam

공식 코드

S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation

https://github.com/jc-78/music2p

공식 코드

Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design

https://github.com/jcruan519/ege-unet

공식 코드

EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation

https://github.com/jcruan519/malunet

공식 코드

MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion Segmentation

https://github.com/jcruan519/mew-unet

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MEW-UNet: Multi-axis representation learning in frequency domain for medical image segmentation

https://github.com/jcruan519/vm-unet

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VM-UNet: Vision Mamba UNet for Medical Image Segmentation

https://github.com/jcwang123/fedlc

공식 코드

Personalizing Federated Medical Image Segmentation via Local Calibration

https://github.com/jefferyjiang-yf/m4oe

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M$^4$oE: A Foundation Model for Medical Multimodal Image Segmentation with Mixture of Experts

https://github.com/jeming-creater/hwa-unetr

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HWA-UNETR: Hierarchical Window Aggregate UNETR for 3D Multimodal Gastric Lesion Segmentation

https://github.com/jeovafarias/teamseg

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Estimating Appearance Models for Image Segmentation via Tensor Factorization

https://github.com/jeroenbertels/deepvoxnet2

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DeepVoxNet2: Yet another CNN framework

https://github.com/jeroenbertels/dicegrad

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The Dice loss in the context of missing or empty labels: Introducing $Φ$ and $ε$

https://github.com/jeya-maria-jose/KiU-Net-pytorch

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KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations

https://github.com/jeya-maria-jose/Medical-Transformer

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Medical Transformer: Gated Axial-Attention for Medical Image Segmentation

https://github.com/jeya-maria-jose/on-the-fly-adaptation

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On-the-Fly Test-time Adaptation for Medical Image Segmentation

https://github.com/jeya-maria-jose/unext-pytorch

공식 코드

UNeXt: MLP-based Rapid Medical Image Segmentation Network

https://github.com/jfzhuang/DAVSS

공식 코드

Video Semantic Segmentation with Distortion-Aware Feature Correction

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