Papers with Code 아카이브

Segmentation

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코드

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

https://github.com/SBU-BMI/quip_cnn_segmentation

공식 코드

Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types

https://github.com/SEAlab-unige/acanet

공식 코드

Affordance segmentation of hand-occluded containers from exocentric images

https://github.com/SHI-Labs/CompFeat-for-Video-Instance-Segmentation

공식 코드

CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation

https://github.com/SHI-Labs/Mask-Selection-Networks

공식 코드

MSN: Efficient Online Mask Selection Network for Video Instance Segmentation

https://github.com/SHI-Labs/Neighborhood-Attention-Transformer

공식 코드

Dilated Neighborhood Attention Transformer

https://github.com/SHI-Labs/OneFormer

공식 코드

OneFormer: One Transformer to Rule Universal Image Segmentation

https://github.com/SHI-Labs/Rethinking-Text-Segmentation

공식 코드

Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

https://github.com/SHI-Labs/SGL-Retinal-Vessel-Segmentation

공식 코드

Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels

https://github.com/SIAAAAAA/MMT-PSM

공식 코드

Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation

https://github.com/SLDGroup/G-CASCADE

공식 코드

G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation

https://github.com/SLDGroup/MERIT

공식 코드

Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation

https://github.com/SMKamrulHasan/Learned-Condensation-Optimizaton-Network

공식 코드

L-CO-Net: Learned Condensation-Optimization Network for Clinical Parameter Estimation from Cardiac Cine MRI

https://github.com/SMKamrulHasan/UNetPlus

공식 코드

U-NetPlus: A Modified Encoder-Decoder U-Net Architecture for Semantic and Instance Segmentation of Surgical Instrument

https://github.com/SRDAMICCAI/SRDA

공식 코드

Source-Relaxed Domain Adaptation for Image Segmentation

https://github.com/SSAW14/LearnableDilationNetwork

공식 코드

Learning Dilation Factors for Semantic Segmentation of Street Scenes

https://github.com/SSAW14/STD2P

공식 코드

STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling

https://github.com/SSAW14/segmentation_membership_inference

공식 코드

Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation

https://github.com/SURA23/Sinus-Surgery-Endoscopic-Image-Datasets

공식 코드

Towards Better Surgical Instrument Segmentation in Endoscopic Vision: Multi-Angle Feature Aggregation and Contour Supervision

https://github.com/SUST-reynole/AMR

공식 코드

Adaptive Morphological Reconstruction for Seeded Image Segmentation

https://github.com/SamMas-hub/Fat-Segmentation-in-MR-using-domain-adaptation

공식 코드

Adipose Tissue Segmentation in Unlabeled Abdomen MRI using Cross Modality Domain Adaptation

https://github.com/SamuelJoutard/Permutohedral_attention_module

공식 코드

Permutohedral Attention Module for Efficient Non-Local Neural Networks

https://github.com/SarderLab/H-AI-L

공식 코드

Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis

https://github.com/Saumya-Gupta-26/struct-uncertainty

공식 코드

Topology-Aware Uncertainty for Image Segmentation

https://github.com/SaverioVad/HAD_Net

공식 코드

HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images

https://github.com/Scatteredrain/SALI

공식 코드

SALI: Short-term Alignment and Long-term Interaction Network for Colonoscopy Video Polyp Segmentation

https://github.com/SehwanChoi0307/Mask2Map

공식 코드

Mask2Map: Vectorized HD Map Construction Using Bird's Eye View Segmentation Masks

https://github.com/Sekunde/3D-SIS

공식 코드

3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans

https://github.com/Semanticity-Research/ARCH2S

공식 코드

ARCH2S: Dataset, Benchmark and Challenges for Learning Exterior Architectural Structures from Point Clouds

https://github.com/Seokju-Cho/Volumetric-Aggregation-Transformer

공식 코드

Cost Aggregation Is All You Need for Few-Shot Segmentation

https://github.com/Seolen/weak_seg_via_shape_model

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Weakly Supervised Volumetric Segmentation via Self-taught Shape Denoising Model

https://github.com/Seung-Hun-Lee/CAVIS

공식 코드

Context-Aware Video Instance Segmentation

https://github.com/Shak97/iceest2019

공식 코드

Heart Segmentation From MRI Scans Using Convolutional Neural Network

https://github.com/ShangHua-Gao/G2L-search

공식 코드

Global2Local: Efficient Structure Search for Video Action Segmentation

https://github.com/ShangHua-Gao/RFNext

공식 코드

RF-Next: Efficient Receptive Field Search for Convolutional Neural Networks

https://github.com/SharifAmit/DilatedFCNSegmentation

공식 코드

Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation

https://github.com/SharifAmit/RVGAN

공식 코드

RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network

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