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/EugeneSel/EUMT
WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia
https://github.com/EvaBr/AnatomyNets
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Everina/car-detection-yolo
https://github.com/EvgenyDyshlyuk/Oil_Seep_Detection
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/EvgenyKashin/SRMnet
SRM : A Style-based Recalibration Module for Convolutional Neural Networks
https://github.com/Expedit-LargeScale-Vision-Transformer/Expedit-SWAG
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning
https://github.com/Eyyub/tensorflow-cyclegan
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/FL77N/Fast-RCNN-on-PPDet
https://github.com/FL77N/RetinaNet-Based-on-PPdet
https://github.com/FMsunyh/keras-yolo2
https://github.com/FaceOnLive/Face-Recognition-SDK-Android
https://github.com/FaceOnLive/License-Plate-Recognition-SDK-Android
A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector
https://github.com/FaceOnLive/Realtime-Background-Changer-SDK-Android
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/FaceOnLive/Spleeter-Android-iOS
The Sound Demixing Challenge 2023 $\unicode{x2013}$ Music Demixing Track
https://github.com/Factral/UnMix-NeRF
Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling
https://github.com/FarihaHossain/SwinFSR
AM-RADIO: Agglomerative Vision Foundation Model -- Reduce All Domains Into One
https://github.com/FarzamIHPC/YoloV3_mask
https://github.com/FateScript/CenterNet-better
https://github.com/FayCai/framework
https://github.com/Fei-dong/SOLO_SORT
https://github.com/FeliMe/multimodal_style_transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/FelixGruen/tensorflow-u-net
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/FenHua/Robust_Logo_Detection
DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
https://github.com/Feynman1999/MgeEditing
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Feynman27/pytorch-detect-rfcn
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/Feynman27/pytorch-detect-to-track
https://github.com/FicmillaR/FicmillaR.github.io
Weighted boxes fusion: Ensembling boxes from different object detection models
https://github.com/FiveEyes/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/FlameRB/Face-Detection-using-Deep-Learning
Multi-view Face Detection Using Deep Convolutional Neural Networks
https://github.com/FloCF/SSL_pytorch
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
https://github.com/FlorentijnD/FairMOT
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/FlorinAndrei/TensorAim
https://github.com/FlowWind1999/pointnet-2
https://github.com/FluteXu/ms-project
RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free
https://github.com/FlyEgle/MAE-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.