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2D Classification

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코드

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

https://github.com/FlyingAnt2018/darknet-modify

YOLOv3: An Incremental Improvement

https://github.com/FlyingRoastDuck/PGPPM

Leveraging Virtual and Real Person for Unsupervised Person Re-identification

https://github.com/ForrestPi/GHM_Loss

Gradient Harmonized Single-stage Detector

https://github.com/FraCorti/Deep_Subnetworks_for_Dynamic_Resource_Constraints

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/FrancescoSaverioZuppichini/ResNet

Deep Residual Learning for Image Recognition

https://github.com/FrancisCrickInstitute/Etch-a-Cell-Nuclear-Envelope

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/FreddeFrallan/Multilingual-CLIP

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/FulminisH/Style-Transfer

A Neural Algorithm of Artistic Style

https://github.com/FurkanGozukara/SpeechSplitTest

Unsupervised Speech Decomposition via Triple Information Bottleneck

https://github.com/Fw9wef/DetectorGAN

Generative Modeling for Small-Data Object Detection

https://github.com/G0rav/Automatic_Background_Removal

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/GAIA-vision/GAIA-det

GAIA: A Transfer Learning System of Object Detection that Fits Your Needs

https://github.com/GANtastic3/MaskCycleGAN-VC

MaskCycleGAN-VC: Learning Non-parallel Voice Conversion with Filling in Frames

https://github.com/GAOwy123/py-faster-rcnn

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

https://github.com/GBATZOLIS/Wespe-Keras

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/GH3927/CycleGAN-applied-to-cranes

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/GH3927/Mask-RCNN-applied-to-cranes

Mask R-CNN

https://github.com/GKalliatakis/Keras-VGG16-places365

Deep Residual Learning for Image Recognition

https://github.com/GPUPhobia/vocal-mask

End-to-end music source separation: is it possible in the waveform domain?

https://github.com/GSNCodes/Neural_Style_Transfer

A Neural Algorithm of Artistic Style

https://github.com/GT-RIPL/L2C

Learning to Cluster for Proposal-Free Instance Segmentation

https://github.com/GXYM/Focal-loss

Focal Loss for Dense Object Detection

https://github.com/GXYM/GHM_Loss

Gradient Harmonized Single-stage Detector

https://github.com/GZQ0723/YoloV4

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/Gabriel-Macias/robust_frcnn

A Robust Learning Approach to Domain Adaptive Object Detection

https://github.com/Gahyeonkim09/AAPL

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/Garfield35/Doodle

A Neural Algorithm of Artistic Style

https://github.com/GarrickZ2/Image-Denoising

Restormer: Efficient Transformer for High-Resolution Image Restoration

https://github.com/GaryMataev/DeepRED

DeepRED: Deep Image Prior Powered by RED

https://github.com/GatorSense/SRrootimaging

Super Resolution for Root Imaging

https://github.com/Gaurav14cs17/YOLOE

Learning Open-World Object Proposals without Learning to Classify

https://github.com/Gaurav927/Neural_Style_Transfer

A Neural Algorithm of Artistic Style

https://github.com/GauthierDmn/question_answering

SQuAD: 100,000+ Questions for Machine Comprehension of Text

https://github.com/GauthierDmn/question_generation

SQuAD: 100,000+ Questions for Machine Comprehension of Text

https://github.com/Gavino7/YOLOv3set

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/Gedeon-m-gedus/compressed_object_detection

Compressed Object Detection

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