Papers with Code 아카이브

2D Semantic Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

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/leonardhan1979/fasterRCNN

Mask R-CNN

https://github.com/leonardoaraujosantos/seg_atrous

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/efficientvit

EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

https://github.com/lewandofskee/MobileMamba

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/lhoyer/DAFormer

Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image Segmentation

https://github.com/lhoyer/mic

Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image Segmentation

https://github.com/li-qingyun/sam-mmrotate

Segment Anything

https://github.com/liangfu/mxnet-mobilenet-v2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/liarba/caffe_dev

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

https://github.com/libiseller/MobileNetV2-dynamicFPN

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/lichengunc/mask-faster-rcnn

Mask R-CNN

https://github.com/lidongliang666/cv_deep_learning

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/lifesailor/data-driven-predictive-maintenance

Deep Learning and Its Applications to Machine Health Monitoring: A Survey

https://github.com/lihaoliu-cambridge/unsupervised-medical-image-segmentation

Contrastive Registration for Unsupervised Medical Image Segmentation

https://github.com/lincaiming/py-faster-rcnn-update

Mask R-CNN

https://github.com/lincaiming/py-faster-rcnn-windows

Mask R-CNN

https://github.com/links-ads/burned-area-seg

Robust Burned Area Delineation through Multitask Learning

https://github.com/lipurple/grounded-diffusion

Open-vocabulary Object Segmentation with Diffusion Models

https://github.com/liuch37/sar-pytorch

Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition

https://github.com/lixiaolei1982/DenseNet-base-Mask-RCNN-for-Human-Pose-Estimation

Mask R-CNN

https://github.com/liyin2015/superpixel_crfasrnn

Conditional Random Fields as Recurrent Neural Networks

https://github.com/ljllili23/unet_baseline

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/llmbev/talk2bev

Talk2BEV: Language-enhanced Bird's-eye View Maps for Autonomous Driving

https://github.com/logictensornetworks/logictensornetworks

Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image Interpretation

https://github.com/lojzezust/lars_evaluator

LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark

https://github.com/longcw/roialign.pytorch

Mask R-CNN

https://github.com/looooongchen/sortedap

Panoptic Segmentation

https://github.com/lordet01/deep_clustering

Deep clustering: Discriminative embeddings for segmentation and separation

https://github.com/lostsword/character_recognition

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/louisfinner/him2sam

SAM 2: Segment Anything in Images and Videos

https://github.com/louisyuzhe/car-damage-detector

Mask R-CNN

https://github.com/lpiccinelli-eth/unidepth

iDisc: Internal Discretization for Monocular Depth Estimation

https://github.com/lpirola13/flower-recognizer

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/lpirola13/flower_recognizer

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/lrr-rachel/PCDUNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ls5122/mask-rcnn

Mask R-CNN

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