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/rezazad68/transnorm

공식 코드

TransNorm: Transformer Provides a Strong Spatial Normalization Mechanism for a Deep Segmentation Model

https://github.com/ricardobnjunior/OctHU-PageScan

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A Fast Fully Octave Convolutional Neural Network for Document Image Segmentation

https://github.com/riced2klab/swim

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A New Dataset and Performance Benchmark for Real-time Spacecraft Segmentation in Onboard Flight Computers

https://github.com/ricklisz/anatomask

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AnatoMask: Enhancing Medical Image Segmentation with Reconstruction-guided Self-masking

https://github.com/ricklisz/polyp-sam

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Polyp-SAM: Transfer SAM for Polyp Segmentation

https://github.com/riddhishb/self-supervised-landmarks

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Leveraging Unsupervised Image Registration for Discovery of Landmark Shape Descriptor

https://github.com/rio98/hybrid-representation-enhanced-bayesian-active-learning

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Hybrid Representation-Enhanced Sampling for Bayesian Active Learning in Musculoskeletal Segmentation of Lower Extremities

https://github.com/risabbiswas/knowledge-distillation-in-medical-image-segmentation

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Multi-Task Multi-Scale Contrastive Knowledge Distillation for Efficient Medical Image Segmentation

https://github.com/risabbiswas/polyp-sam

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Polyp-SAM++: Can A Text Guided SAM Perform Better for Polyp Segmentation?

https://github.com/rkzheng99/villa

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ViLLa: Video Reasoning Segmentation with Large Language Model

https://github.com/robbergen/trgan

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Assessing Privacy Leakage in Synthetic 3-D PET Imaging using Transversal GAN

https://github.com/robert80203/GSVNet

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GSVNet: Guided Spatially-Varying Convolution for Fast Semantic Segmentation on Video

https://github.com/robustml-eurecom/Vessel-Captcha

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Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation

https://github.com/robustml-eurecom/quality_control_CMR

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Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation

https://github.com/robustsam/RobustSAM

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RobustSAM: Segment Anything Robustly on Degraded Images

https://github.com/rohit-kundu/ideal-icassp23

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IDEAL: Improved DEnse locAL Contrastive Learning for Semi-Supervised Medical Image Segmentation

https://github.com/rongzhao-zhang/ag-crc

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AG-CRC: Anatomy-Guided Colorectal Cancer Segmentation in CT with Imperfect Anatomical Knowledge

https://github.com/rongzhou7/ttt-unet

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TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation

https://github.com/rosanajurdi/prior-based-losses-for-medical-image-segmentation

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Effect of Prior-based Losses on Segmentation Performance: A Benchmark

https://github.com/rows21/dk-uxnet

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Semi-supervised Medical Image Segmentation via Query Distribution Consistency

https://github.com/rstrudel/segmenter

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Segmenter: Transformer for Semantic Segmentation

https://github.com/rt219/the-emergence-of-objectness

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The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos

https://github.com/rubics-xuan/fremim

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FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation

https://github.com/ruirangerfan/road_crack_detection_net

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Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding

https://github.com/ruizhe-l/semi-segmentation

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A generic ensemble based deep convolutional neural network for semi-supervised medical image segmentation

https://github.com/runminjiang/pw4medseg

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Enhancing Weakly Supervised 3D Medical Image Segmentation through Probabilistic-aware Learning

https://github.com/ruochengao/swin_litemedsam

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Swin-LiteMedSAM: A Lightweight Box-Based Segment Anything Model for Large-Scale Medical Image Datasets

https://github.com/rusu4943/3d-sfuda

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Cross-Domain Distribution Alignment for Segmentation of Private Unannotated 3D Medical Images

https://github.com/rwightman/pytorch-image-models

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How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

https://github.com/ryersonmultimedialab/dynaseg

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DynaSeg: A Deep Dynamic Fusion Method for Unsupervised Image Segmentation Incorporating Feature Similarity and Spatial Continuity

https://github.com/ryh1218/occ

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Prohibited Items Segmentation via Occlusion-aware Bilayer Modeling

https://github.com/s-sd/spurl

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Competing for pixels: a self-play algorithm for weakly-supervised segmentation

https://github.com/saadwazir/HistoSeg

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HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images

https://github.com/saadwazir/ReN-UNet

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Rethinking the Nested U-Net Approach: Enhancing Biomarker Segmentation with Attention Mechanisms and Multiscale Feature Fusion

https://github.com/saadwazir/mcads-decoder

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Rethinking Decoder Design: Improving Biomarker Segmentation Using Depth-to-Space Restoration and Residual Linear Attention

https://github.com/sadjadrz/Lung-segmentation-dataset

공식 코드

FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation

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