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/dmarcosg/DSAC

공식 코드

Learning deep structured active contours end-to-end

https://github.com/dmcv-ecnu/MindSpore_ModelZoo

공식 코드

Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud

https://github.com/dmitrii-marin/robust_trust_region

공식 코드

Robust Trust Region for Weakly Supervised Segmentation

https://github.com/dmlc/gluon-cv

공식 코드

Bag of Tricks for Image Classification with Convolutional Neural Networks

https://github.com/dmmm1997/c3vg

공식 코드

Multi-task Visual Grounding with Coarse-to-Fine Consistency Constraints

https://github.com/dmtjepa/dmtjepa

공식 코드

DMT-JEPA: Discriminative Masked Targets for Joint-Embedding Predictive Architecture

https://github.com/dmytro-shvetsov/counterfactual-search

공식 코드

COIN: Counterfactual inpainting for weakly supervised semantic segmentation for medical images

https://github.com/dnjs3594/Eigencontours

공식 코드

Eigencontours: Novel Contour Descriptors Based on Low-Rank Approximation

https://github.com/dogabasaran/lesion-synthesis

공식 코드

Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images

https://github.com/dogabasaran/lesionmix

공식 코드

LesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation

https://github.com/dogehhh/reclip

공식 코드

ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation

https://github.com/dom3442/leafonlysam

공식 코드

Leaf Only SAM: A Segment Anything Pipeline for Zero-Shot Automated Leaf Segmentation

https://github.com/dong-huo/rgb-t-glass-segmentation

공식 코드

Glass Segmentation with RGB-Thermal Image Pairs

https://github.com/dong03/MVSS-Net

공식 코드

Image Manipulation Detection by Multi-View Multi-Scale Supervision

https://github.com/dong845/mcp-medsam

공식 코드

MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model Trained with a Single GPU in Just One Day

https://github.com/dongbo811/afformer

공식 코드

Head-Free Lightweight Semantic Segmentation with Linear Transformer

https://github.com/dongbo811/uqformer

공식 코드

A Unified Query-based Paradigm for Camouflaged Instance Segmentation

https://github.com/donggeun-yoon/dcp

공식 코드

Lightweight Alpha Matting Network Using Distillation-Based Channel Pruning

https://github.com/donghao51/awesome-multimodal-adaptation

공식 코드

Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models

https://github.com/donglaiw/AxonEM-challenge

공식 코드

AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions

https://github.com/donglao/PCEDA

공식 코드

Phase Consistent Ecological Domain Adaptation

https://github.com/donglao/depthtosemantic

공식 코드

On the Viability of Monocular Depth Pre-training for Semantic Segmentation

https://github.com/donglao/srt

공식 코드

Sub-token ViT Embedding via Stochastic Resonance Transformers

https://github.com/donnyyou/torchcv

공식 코드

Asymmetric Non-local Neural Networks for Semantic Segmentation

https://github.com/dootmaan/mt-unet

공식 코드

Mixed Transformer U-Net For Medical Image Segmentation

https://github.com/dootmaan/pfseg-full

공식 코드

Super-Resolution Based Patch-Free 3D Image Segmentation with High-Frequency Guidance

https://github.com/doranlyong/spanetv2-official

공식 코드

Spectral-Adaptive Modulation Networks for Visual Perception

https://github.com/dorltcheng/Transfer-Learning-U-Net-Deep-Learning-for-Lung-Ultrasound-Segmentation

공식 코드

Transfer Learning U-Net Deep Learning for Lung Ultrasound Segmentation

https://github.com/dosowiechi/mlmp

공식 코드

Test-Time Adaptation of Vision-Language Models for Open-Vocabulary Semantic Segmentation

https://github.com/dota-109/Web-WILSS

공식 코드

Learning from the Web: Language Drives Weakly-Supervised Incremental Learning for Semantic Segmentation

https://github.com/douglas2code/text2seg

공식 코드

Text2Seg: Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models

https://github.com/douyimin/faultnet

공식 코드

MD Loss: Efficient Training of 3D Seismic Fault Segmentation Network under Sparse Labels by Weakening Anomaly Annotation

https://github.com/dpbenalcazar/ArtificialDilation

공식 코드

Artificial Pupil Dilation for Data Augmentation in Iris Semantic Segmentation

https://github.com/dragondescentzerotsu/ssm-sam

공식 코드

Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learning

https://github.com/drainingsun/ybat

공식 코드

Classifying Breast Histopathology Images with a Ductal Instance-Oriented Pipeline

https://github.com/drchip61/mas-sam

공식 코드

MAS-SAM: Segment Any Marine Animal with Aggregated Features

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