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/minghanz/DepthC3D

Digging Into Self-Supervised Monocular Depth Estimation

https://github.com/mingxingtan/mnasnet

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/minimaxir/person-blocker

Microsoft COCO: Common Objects in Context

https://github.com/minus31/Portrait-segmentation

Fast-SCNN: Fast Semantic Segmentation Network

https://github.com/miquel-espinosa/samantics

No time to train! Training-Free Reference-Based Instance Segmentation

https://github.com/mirnadaye/Brain_Tumor_Project

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/mirzaevinom/data_science_bowl_2018

Mask R-CNN

https://github.com/mit-han-lab/sparsevit

SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer

https://github.com/mitmedialab/unet4birds

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/mkara44/transunet_pytorch

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

https://github.com/mkara44/unetr_pytorch

UNETR: Transformers for 3D Medical Image Segmentation

https://github.com/mkimhi/RISE

In Defense of Online Models for Video Instance Segmentation

https://github.com/mlearing/pytorch-deeplab-v3-plus

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

https://github.com/mmasana/FACIL

Learning without Forgetting

https://github.com/mmfrxx/X-net

XNet: A convolutional neural network (CNN) implementation for medical X-Ray image segmentation suitable for small datasets

https://github.com/mmheydari97/BCDU-Net

Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions

https://github.com/mobarakol/SVLS

Spatially Varying Label Smoothing: Capturing Uncertainty from Expert Annotations

https://github.com/modelhub-ai/mobilenet

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/moelgendy/mobileNetV2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/moh833/VQA

Exploring Models and Data for Image Question Answering

https://github.com/mohsenkheirandishfard/IS4

Image Segmentation using Sparse Subset Selection

https://github.com/mohuazheliu/ResUnet-a

ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data

https://github.com/momih/pc-hemis

HeMIS: Hetero-Modal Image Segmentation

https://github.com/montescene/demo

Monte Carlo Scene Search for 3D Scene Understanding

https://github.com/motlabs/dont-be-turtle

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/moto8xpk/DataExtractionJejuMLCamp

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

https://github.com/moucheng2017/learning_morphological_perturbation_ssl

Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation

https://github.com/mpariente/asteroid

Deep clustering: Discriminative embeddings for segmentation and separation

https://github.com/mrgiovanni/dissertation

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/mrkolarik/3d-brain-segmentation

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

https://github.com/mrmtn86/python1

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/mrvturan96/Brain-Tumor-Detection-and-Segmentation-using-Deep-Learning

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/mrzaizai2k/Information-recognition-on-the-university-test-paper

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

https://github.com/mseg-dataset/mseg-api

MSeg: A Composite Dataset for Multi-domain Semantic Segmentation

https://github.com/msminhas93/deeplabv3finetuning

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/mssung94/intel-image-classification

MobileNetV2: Inverted Residuals and Linear Bottlenecks

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