Papers with Code 아카이브

16k

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

6

평가표

1

보존된 평가 기록

1

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/JonathanLehner/TecoGan-downloader

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

https://github.com/Jongchan/attention-module

CBAM: Convolutional Block Attention Module

https://github.com/Jonydom/Faster-RCNN

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

https://github.com/Joostdambrink/GeniusAI

Enhanced Deep Residual Networks for Single Image Super-Resolution

https://github.com/Jorge-Mendes/darknet-google-colab

YOLOv3: An Incremental Improvement

https://github.com/JosephPB/XNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/JoshuaPlacidi/MS-COCO-Object-Tags

VinVL: Revisiting Visual Representations in Vision-Language Models

https://github.com/JoshuaPlacidi/MS-COCO-Tags

VinVL: Revisiting Visual Representations in Vision-Language Models

https://github.com/Josien94/MLiP

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/JoyHsiao/Haitec

SSD: Single Shot MultiBox Detector

https://github.com/Joyce511/OpenVino_Realtime_Multi-Person_Pose_Estimation

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/JuliaChae/M3D-RPN-Waymo

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/JunaidCS032/MOTBeyondPixels

Accurate Single Stage Detector Using Recurrent Rolling Convolution

https://github.com/JungminChung/Korean_Struc_Det

Objects as Points

https://github.com/JunnYu/x-transformers-paddle

End-to-End Object Detection with Transformers

https://github.com/JunshengFu/vehicle-detection

You Only Look Once: Unified, Real-Time Object Detection

https://github.com/JunweiLiang/Object_Detection_Tracking

Relation Networks for Object Detection

https://github.com/JunweiLiang/aicity_action

MViTv2: Improved Multiscale Vision Transformers for Classification and Detection

https://github.com/K-Mike/Automatic-salt-deposits-segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/KGML-lab/Generalized-Forward-Inverse-Framework-for-DL4SI

MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments

https://github.com/KMnP/fashionpedia-api

Mask R-CNN

https://github.com/KPMG-wiseuniv/AI

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/KUR-creative/SickZil-Machine

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/KaFaiFai/MobileNet-PyTorch

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/KaFaiFai/MobileNet-PyTorch-Converter

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/KaidongLi/tf-3d-alpha

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

https://github.com/Kaif10/Pose-Detection

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/KaimingHe/deep-residual-networks

Deep Residual Learning for Image Recognition

https://github.com/KangJier/polarMask

PolarMask: Single Shot Instance Segmentation with Polar Representation

https://github.com/Karan-kapadia/Style-Transfer-karan

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/KarimDahawy/CapStone-Project

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/KarimaCha/CNN_Trust_Prediction

Deep Residual Learning for Image Recognition

https://github.com/KarinaKorsgaard/Bartender-AI-OpenPose-Osc-Sender

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/KarthikDulam/U-NetCNN

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Kartik-Aggarwal/Real-Time-Traffic-Sign-Detection

You Only Look Once: Unified, Real-Time Object Detection

https://github.com/KatherineBaq/NMA-CN2021-fMRI_vs_DNNs

Deep Residual Learning for Image Recognition

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