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/vineet2104/hifics

Segment Anything

https://github.com/violin0847/crowdcounting

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

https://github.com/vios-s/adversarial-test-time-training

Re-using Adversarial Mask Discriminators for Test-time Training under Distribution Shifts

https://github.com/vios-s/multiscale-adversarial-attention-gates

Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates

https://github.com/visaVita/mmaction2

Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective

https://github.com/vishwesh5/Paper-a-day

OCNet: Object Context Network for Scene Parsing

https://github.com/vitae-transformer/samrs

Segment Anything

https://github.com/vitalab/castor

Cardiac Segmentation with Strong Anatomical Guarantees

https://github.com/vivaan-park/where-is-wally

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

https://github.com/vlar-group/unmore

CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised Transformers

https://github.com/vlcekl/n2n-tomo

Microsoft COCO: Common Objects in Context

https://github.com/vlievin/Unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/void-in-the-matrix/nuclei-segmentation-unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/voidrank/SaccadeNet

SaccadeNet: A Fast and Accurate Object Detector

https://github.com/vpariza/open-hummingbird-eval

Towards In-context Scene Understanding

https://github.com/vqdang/hover_net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/vqdang/xy_net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/vsitzmann/light-field-networks

Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering

https://github.com/vwegn/dm

Fully-Trainable Deep Matching

https://github.com/w5688414/Keras-MobileNetV2-Image-classification

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/wacr2008/tensorflow_crnn

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

https://github.com/waggle-sensor/plugin-water-detector

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

https://github.com/wang-chen/SubT

Visual Memorability for Robotic Interestingness via Unsupervised Online Learning

https://github.com/wang-chen/interestingness_ros

Visual Memorability for Robotic Interestingness via Unsupervised Online Learning

https://github.com/wang-wg/DeepStroke

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

https://github.com/wangguangyuan/ClusterContrast

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

https://github.com/wangjinzhuo/wearables

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging

https://github.com/wangleihitcs/DeepLab-V1-PyTorch

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

https://github.com/wanglibing727/DAN_pytorch

Decoupled Attention Network for Text Recognition

https://github.com/wangrui1996/crnnLicensePlateRecognition

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

https://github.com/wangvation/torch-mobilenet

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/wangyi111/international-archaeology-ai-challenge

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/wangys16/freesplat

FreeSplat++: Generalizable 3D Gaussian Splatting for Efficient Indoor Scene Reconstruction

https://github.com/wangyuan249/Mymmt767

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

https://github.com/wannabeOG/ExpertNet-Pytorch

Learning without Forgetting

https://github.com/warmspringwinds/pytorch-segmentation-detection

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

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