Papers with Code 아카이브

Semantic Segmentation

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전체 기법전체 데이터셋

하위 태스크

29

평가표

150

보존된 평가 기록

1,918

코드

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

https://github.com/nihalsid/ViewAL

공식 코드

ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation

https://github.com/nii-yamagishilab/fashion_adv

공식 코드

Fashion-Guided Adversarial Attack on Person Segmentation

https://github.com/nii-yamagishilab/ssl_vits_df

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Exploring Self-Supervised Vision Transformers for Deepfake Detection: A Comparative Analysis

https://github.com/nikhel1/gal-cam

공식 코드

Deep Learning for Morphological Identification of Extended Radio Galaxies using Weak Labels

https://github.com/nikhilroxtomar/DDANet

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DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation

https://github.com/nikhilroxtomar/fanet

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FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation

https://github.com/nikhilroxtomar/tganet

공식 코드

TGANet: Text-guided attention for improved polyp segmentation

https://github.com/niko-k98/awesome-list-federated-learning-review

공식 코드

Privacy Preserving Federated Learning in Medical Imaging with Uncertainty Estimation

https://github.com/nikolai10/egic

공식 코드

EGIC: Enhanced Low-Bit-Rate Generative Image Compression Guided by Semantic Segmentation

https://github.com/nikolaiwarner7/text-and-click-for-open-vocabulary-segmentation

공식 코드

Text and Click inputs for unambiguous open vocabulary instance segmentation

https://github.com/nikolasmorshuis/sgr

공식 코드

Segmentation-guided MRI reconstruction for meaningfully diverse reconstructions

https://github.com/niladridutt/Diffusion-3D-Features

공식 코드

Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features

https://github.com/niloide/implicit_segmentation

공식 코드

NISF: Neural Implicit Segmentation Functions

https://github.com/nina-weng/shortcut_skinseg

공식 코드

Shortcut Learning in Medical Image Segmentation

https://github.com/nitr098/attswinunet

공식 코드

Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion Segmentation

https://github.com/nitr098/awesome-u-net

공식 코드

Medical Image Segmentation Review: The success of U-Net

https://github.com/nizhenliang/RAUNet

공식 코드

RAUNet: Residual Attention U-Net for Semantic Segmentation of Cataract Surgical Instruments

https://github.com/nizhenliang/cgrseg

공식 코드

Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation

https://github.com/njuhuojing/mast

공식 코드

Manifold Alignment for Semantically Aligned Style Transfer

https://github.com/nki-radiology/interpretability_augmentation

공식 코드

Interpretability-guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data

https://github.com/nkicsl/sf-unet

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Spatial-Frequency Dual Progressive Attention Network For Medical Image Segmentation

https://github.com/nkuhealong/pmcnet

공식 코드

Progressive Multi-scale Consistent Network for Multi-class Fundus Lesion Segmentation

https://github.com/nkusyl/evit

공식 코드

EViT: An Eagle Vision Transformer with Bi-Fovea Self-Attention

https://github.com/nmaac/acon

공식 코드

Activate or Not: Learning Customized Activation

https://github.com/nmndeep/robust-segmentation

공식 코드

Towards Reliable Evaluation and Fast Training of Robust Semantic Segmentation Models

https://github.com/nnizhang/SMAC

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Specificity-preserving RGB-D Saliency Detection

https://github.com/nnnth/UFO

공식 코드

UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface

https://github.com/nobodyplayer1/vm-unetv2

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VM-UNET-V2 Rethinking Vision Mamba UNet for Medical Image Segmentation

https://github.com/noelshin/namedmask

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NamedMask: Distilling Segmenters from Complementary Foundation Models

https://github.com/noelshin/selfmask

공식 코드

Unsupervised Salient Object Detection with Spectral Cluster Voting

https://github.com/noelshin/zutis

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Zero-shot Unsupervised Transfer Instance Segmentation

https://github.com/norlab-ulaval/logpiles_segmentation

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Instance Segmentation for Autonomous Log Grasping in Forestry Operations

https://github.com/notmahi/clip-fields

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CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory

https://github.com/notmatthancock/level-set-machine-learning

공식 코드

Level set image segmentation with velocity term learned from data with applications to lung nodule segmentation

https://github.com/noureddinekhiati/semi-supervised-lung-segmentation

공식 코드

Shape-aware synthesis of pathological lung CT scans using CycleGAN for enhanced semi-supervised lung segmentation

https://github.com/novicefodder/os-medseg

공식 코드

Distillation Learning Guided by Image Reconstruction for One-Shot Medical Image Segmentation

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