Papers with Code 아카이브

2D Semantic Segmentation

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하위 태스크

17

평가표

11

보존된 평가 기록

42

코드

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

https://github.com/juntang-zhuang/LadderNet

공식 코드

LadderNet: Multi-path networks based on U-Net for medical image segmentation

https://github.com/juntang-zhuang/ShelfNet

공식 코드

ShelfNet for Fast Semantic Segmentation

https://github.com/juntang-zhuang/ShelfNet-lw-cityscapes

공식 코드

ShelfNet for Fast Semantic Segmentation

https://github.com/juntaojianggavin/lv-unet

공식 코드

LV-UNet: A Lightweight and Vanilla Model for Medical Image Segmentation

https://github.com/juntaojianggavin/rwkv-unet

공식 코드

RWKV-UNet: Improving UNet with Long-Range Cooperation for Effective Medical Image Segmentation

https://github.com/juntongkuki/pytorch-dsfnet

공식 코드

DSFNet: Dual-GCN and Location-fused Self-attention with Weighted Fast Normalized Fusion for Polyps Segmentation

https://github.com/junyuchen245/Semi-supervised_FCM_Loss_for_Segmentation

공식 코드

Learning Fuzzy Clustering for SPECT/CT Segmentation via Convolutional Neural Networks

https://github.com/junyuchen245/Unsuprevised_Seg_via_CNN

공식 코드

Medical Image Segmentation via Unsupervised Convolutional Neural Network

https://github.com/junyuchen245/ViT-V-Net_for_3D_Image_Registration_Pytorch

공식 코드

ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration

https://github.com/junzis/contrail-net

공식 코드

Flight Contrail Segmentation via Augmented Transfer Learning with Novel SR Loss Function in Hough Space

https://github.com/jupitern52/textbrats

공식 코드

TextBraTS: Text-Guided Volumetric Brain Tumor Segmentation with Innovative Dataset Development and Fusion Module Exploration

https://github.com/jusiro/fewshot-finetuning

공식 코드

Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ Segmentation

https://github.com/justlfc03/dfcps

공식 코드

Semi-supervised Medical Image Segmentation Method Based on Cross-pseudo Labeling Leveraging Strong and Weak Data Augmentation Strategies

https://github.com/justlfc03/scunet-plusplus

공식 코드

SCUNet++: Swin-UNet and CNN Bottleneck Hybrid Architecture with Multi-Fusion Dense Skip Connection for Pulmonary Embolism CT Image Segmentation

https://github.com/justusschock/shapenet

공식 코드

Super-realtime facial landmark detection and shape fitting by deep regression of shape model parameters

https://github.com/jvwilliams23/pyssam

공식 코드

pyssam -- a Python library for statistical modelling of biomedical shape and appearance

https://github.com/jw-chae/sjtu

공식 코드

SJTU:Spatial judgments in multimodal models towards unified segmentation through coordinate detection

https://github.com/jwc-rad/mislight

공식 코드

Knowledge Distillation from Cross Teaching Teachers for Efficient Semi-Supervised Abdominal Organ Segmentation in CT

https://github.com/jwfangit/gate-dap

공식 코드

Gated Driver Attention Predictor

https://github.com/jwicaksana/fedmix

공식 코드

FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation

https://github.com/jyhong0304/visual-relationship-detection-rwfn

공식 코드

Representing Prior Knowledge Using Randomly, Weighted Feature Networks for Visual Relationship Detection

https://github.com/jzengust/RGBD2Normal

공식 코드

Deep Surface Normal Estimation with Hierarchical RGB-D Fusion

https://github.com/k-radlak/IDCNN

공식 코드

Deep Learning based Switching Filter for Impulsive Noise Removal in Color Images

https://github.com/kabbas570/cams-net

공식 코드

CAMS: Convolution and Attention-Free Mamba-based Cardiac Image Segmentation

https://github.com/kabbas570/compseg-metadata

공식 코드

Compositional Segmentation of Cardiac Images Leveraging Metadata

https://github.com/kabbas570/crocnet

공식 코드

Crop and Couple: cardiac image segmentation using interlinked specialist networks

https://github.com/kagawa588/diffvsgg

공식 코드

DIFFVSGG: Diffusion-Driven Online Video Scene Graph Generation

https://github.com/kagawa588/gvseg

공식 코드

General and Task-Oriented Video Segmentation

https://github.com/kai422/covos

공식 코드

Accelerating Video Object Segmentation with Compressed Video

https://github.com/kailaisun/indoor-depth-completion

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A Two-Stage Masked Autoencoder Based Network for Indoor Depth Completion

https://github.com/kainmueller-lab/arctique

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Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification

https://github.com/kainmueller-lab/tw-autoencoder

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Model Guidance via Explanations Turns Image Classifiers into Segmentation Models

https://github.com/kaiseem/dar-unet

공식 코드

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

https://github.com/kaiseem/slaug

공식 코드

Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation

https://github.com/kaland313/ssl-medseg

공식 코드

Self-Supervised Pretraining for 2D Medical Image Segmentation

https://github.com/kalrfou/gctx-unet

공식 코드

GCtx-UNet: Efficient Network for Medical Image Segmentation

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