Papers with Code 아카이브

2D Classification

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코드

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

https://github.com/CLUEbenchmark/LGEB

Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering

https://github.com/CMU-Perceptual-Computing-Lab/openpose_caffe_train

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

https://github.com/CMU-Perceptual-Computing-Lab/openpose_train

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

https://github.com/CMU-Perceptual-Computing-Lab/openpose_unity_plugin

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

https://github.com/COAOX/Cifar-Prototypical

Prototypical Networks for Few-shot Learning

https://github.com/CODEJIN/AutoVC

AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss

https://github.com/CODEJIN/GST_Tacotron

Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis

https://github.com/CODEJIN/SPEECHSPLIT

Unsupervised Speech Decomposition via Triple Information Bottleneck

https://github.com/CRIGIM/darknet

YOLOv3: An Incremental Improvement

https://github.com/CS-GangXu/TMNet

Deformable ConvNets v2: More Deformable, Better Results

https://github.com/CS2470FinalProject/X-GAN

XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings

https://github.com/CSAILVision/semantic-segmentation-pytorch

Pyramid Scene Parsing Network

https://github.com/CSAILVision/unifiedparsing

Acquisition of Localization Confidence for Accurate Object Detection

https://github.com/CSSFA123/yolov4-Road

Scaled-YOLOv4: Scaling Cross Stage Partial Network

https://github.com/CUAI-CAU/Computer_vision_team_1

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

https://github.com/CUHK-AIM-Group/LGS

Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery

https://github.com/CV-deeplearning/caffe

SSD: Single Shot MultiBox Detector

https://github.com/CV51GO/GFLv2_Megengine

Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection

https://github.com/CV51GO/HarDNet_Megengine

HarDNet: A Low Memory Traffic Network

https://github.com/CV51GO/OTA_Megengine

OTA: Optimal Transport Assignment for Object Detection

https://github.com/CV51GO/PAA_Megengine

Probabilistic Anchor Assignment with IoU Prediction for Object Detection

https://github.com/CVUsers/Smart-Retail-By-Efficientdet

Feature Pyramid Networks for Object Detection

https://github.com/CVxTz/face_age_gender

Deep Residual Learning for Image Recognition

https://github.com/CYetlanezi/Proyecto-Opti

A Neural Algorithm of Artistic Style

https://github.com/CZQ0707/mindspore

YOLOv3: An Incremental Improvement

https://github.com/Cadden/paddle-adver

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/CahideSara/deneme

YOLO9000: Better, Faster, Stronger

https://github.com/CaiYingFeng/darknet_changed

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/CallHoganZhang/unet-medical_segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Calylyli/Mindsporehrnet

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/Camebush/real-time-yolov4-object-detection

Rich feature hierarchies for accurate object detection and semantic segmentation

https://github.com/CandiceD17/Bottleneck-Transformers-for-Visual-Recognition

Bottleneck Transformers for Visual Recognition

https://github.com/CanshangD/ResNet_tensorflow2.0

Deep Residual Learning for Image Recognition

https://github.com/Capino512/pytorch-rotation-decoupled-detector

https://github.com/Capsar/DL-GenISP

GenISP: Neural ISP for Low-Light Machine Cognition

https://github.com/CarkusL/CenterPoint

Center-based 3D Object Detection and Tracking

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