Papers with Code 아카이브

Image Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/att100/ucloudnet

공식 코드

UCloudNet: A Residual U-Net with Deep Supervision for Cloud Image Segmentation

https://github.com/auroua/hrstnet

공식 코드

High-Resolution Swin Transformer for Automatic Medical Image Segmentation

https://github.com/autogluon/autogluon

공식 코드

Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

https://github.com/avc2-uestc/qmedsam

공식 코드

Efficient Quantization-Aware Training on Segment Anything Model in Medical Images and Its Deployment

https://github.com/avm-debatr/bagganhq

공식 코드

Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN Images

https://github.com/avm-debatr/ganecdotes

공식 코드

Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN Images

https://github.com/awadelrahman/medai

공식 코드

Explainable Medical Image Segmentation via Generative Adversarial Networks and Layer-wise Relevance Propagation

https://github.com/axi404/pmt

공식 코드

PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation

https://github.com/ayushroy2001/gru-net

공식 코드

GRU-Net: Gaussian Attention Aided Dense Skip Connection Based MultiResUNet for Breast Histopathology Image Segmentation

https://github.com/azadef/ynet

공식 코드

Y-Net: A Spatiospectral Dual-Encoder Networkfor Medical Image Segmentation

https://github.com/azuma164/zodi

공식 코드

ZoDi: Zero-Shot Domain Adaptation with Diffusion-Based Image Transfer

https://github.com/baai-dcai/segvol

공식 코드

SegVol: Universal and Interactive Volumetric Medical Image Segmentation

https://github.com/backpropagator/langdaug

공식 코드

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation

https://github.com/bahramjafrasteh/melage

공식 코드

MELAGE: A purely python based Neuroimaging software (Neonatal)

https://github.com/bahramjafrasteh/mga-net

공식 코드

Mask-Guided Attention U-Net for Enhanced Neonatal Brain Extraction and Image Preprocessing

https://github.com/baiwenjia/CIMAS

공식 코드

Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach

https://github.com/bala93/marginloss

공식 코드

Calibrating Segmentation Networks with Margin-based Label Smoothing

https://github.com/balbasty/nitorch

공식 코드

An MRF-UNet Product of Experts for Image Segmentation

https://github.com/bangwayne/verse

공식 코드

VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation

https://github.com/baobao0926/asp-vmunet

공식 코드

ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion Segmentation

https://github.com/baumgach/PHiSeg-code

공식 코드

PHiSeg: Capturing Uncertainty in Medical Image Segmentation

https://github.com/baumgach/acdc_segmenter

공식 코드

An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation

https://github.com/beginner-cjh/medvkan

공식 코드

MedVKAN: Efficient Feature Extraction with Mamba and KAN for Medical Image Segmentation

https://github.com/beileicui/ms-tfal

공식 코드

Rectifying Noisy Labels with Sequential Prior: Multi-Scale Temporal Feature Affinity Learning for Robust Video Segmentation

https://github.com/benjamintowle/seqsam

공식 코드

SeqSAM: Autoregressive Multiple Hypothesis Prediction for Medical Image Segmentation using SAM

https://github.com/benjamintowle/simsam

공식 코드

SimSAM: Zero-shot Medical Image Segmentation via Simulated Interaction

https://github.com/benolmbrt/wcp_miccai

공식 코드

Robust Conformal Volume Estimation in 3D Medical Images

https://github.com/berkeley-hipie/hipie

공식 코드

Hierarchical Open-vocabulary Universal Image Segmentation

https://github.com/berkels/msiplib

공식 코드

A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentation

https://github.com/bermanmaxim/LovaszSoftmax

공식 코드

The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks

https://github.com/bermanmaxim/superpixPool

공식 코드

Efficient semantic image segmentation with superpixel pooling

https://github.com/bev-gorry/underloc

공식 코드

Image-Based Relocalization and Alignment for Long-Term Monitoring of Dynamic Underwater Environments

https://github.com/biclab/spike2former

공식 코드

Spike2Former: Efficient Spiking Transformer for High-performance Image Segmentation

https://github.com/billhhh/ShaSpec

공식 코드

Multi-modal Learning with Missing Modality via Shared-Specific Feature Modelling

https://github.com/bingogome/samm

공식 코드

SAMM (Segment Any Medical Model): A 3D Slicer Integration to SAM

https://github.com/binycn/dcpa

공식 코드

Dual-Decoder Consistency via Pseudo-Labels Guided Data Augmentation for Semi-Supervised Medical Image Segmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.