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/kevinddchen/Keras-FCN

Fully Convolutional Networks for Semantic Segmentation

https://github.com/keyEpoch/semen_seg-kd

Semantic Understanding of Scenes through the ADE20K Dataset

https://github.com/khanlab/hippunfold

On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

https://github.com/kibok90/iccv2019-inc

Learning without Forgetting

https://github.com/kikacaty/RAP_Benchmark

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

https://github.com/kilgore92/Probabalistic-U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kilgore92/PyTorch-UNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kim-younghan/FEELVOS

FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

https://github.com/kimdesok/UNet_2D_Semantic_Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kingcong/PSPNet

Pyramid Scene Parsing Network

https://github.com/kingcong/mobilenetv2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/kingcong/vit

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

https://github.com/kingo233/FCT-Pytorch

The Fully Convolutional Transformer for Medical Image Segmentation

https://github.com/kingyiusuen/image-to-latex

Full Page Handwriting Recognition via Image to Sequence Extraction

https://github.com/kini5gowda/ALBA-RL-for-VOS

ALBA : Reinforcement Learning for Video Object Segmentation

https://github.com/kkhosla96/cs231n-project

Microsoft COCO: Common Objects in Context

https://github.com/kklemon/bgan-pytorch

Boundary-Seeking Generative Adversarial Networks

https://github.com/klin059/lits

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kmaninis/COB

Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks

https://github.com/kmaninis/OSVOS-PyTorch

One-Shot Video Object Segmentation

https://github.com/kmaninis/OSVOS-caffe

One-Shot Video Object Segmentation

https://github.com/kmswlee/ainized-PointRend

PointRend: Image Segmentation as Rendering

https://github.com/konny0311/unet_segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/koriavinash1/DigitalHistoPath

A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and Analysis

https://github.com/koriavinash1/Fetal-Brain-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kornia/kornia

Segment Anything

https://github.com/koryako/AI-application

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation

https://github.com/koshian2/OctConv-TFKeras

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kpullak/DefectSegmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/krantirk/py-faster-rcnn

Mask R-CNN

https://github.com/krishnapalS/Human-Pose-Estimation-using-ShelfNet

ShelfNet for Fast Semantic Segmentation

https://github.com/kritanu82/healthif.ai

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/krutikabapat/Crowd_Counting

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

https://github.com/kshitij1489/object-tracking

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/kshitizrimal/Fast-SCNN

Fast-SCNN: Fast Semantic Segmentation Network

https://github.com/kskim-phd/mfcn

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation

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