https://github.com/BR-IDL/PaddleViT/tree/develop/image_classification/Focal_Transformer
Focal Self-attention for Local-Global Interactions in Vision Transformers
Papers with Code 아카이브
2D Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BR-IDL/PaddleViT/tree/develop/image_classification/HaloNet
Scaling Local Self-Attention for Parameter Efficient Visual Backbones
https://github.com/BR-IDL/PaddleViT/tree/develop/image_classification/MobileOne
https://github.com/BR-IDL/PaddleViT/tree/develop/image_classification/MobileViT
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
https://github.com/BR-IDL/PaddleViT/tree/develop/image_classification/PiT
https://github.com/BR-IDL/PaddleViT/tree/develop/image_classification/XCiT
https://github.com/BR-IDL/PaddleViT/tree/develop/self_supervised_learning/dino
https://github.com/BUPT-PRIV/MAE-priv
https://github.com/Baibaifan/An-Improved-PeleeNet-Algorithm-with-Feature-Pyramid-Networks-for-Image-Detection-
https://github.com/Baichenjia/Resnet
https://github.com/BaiqingL/CS523-Final
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Bakikii/stylegan2-pytorch23
https://github.com/BaladityaY/lemniscate_reproduce_bdd
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
https://github.com/BaladityaY/lemniscate_vis
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
https://github.com/BalajiAI/PyTorch-GAN/tree/main/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Bangbangbanana/fairmot_mindspore
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/Banus/caffe-demo
https://github.com/Bao-Jiarong/ResNet
https://github.com/Barak123748596/CVDL_course_project
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Bartzi/one-model-to-reconstruct-them-all
https://github.com/BboyHanat/U-Net
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/BearCooike/ssFPN-pytorch
ssFPN: Scale Sequence (S^2) Feature Based-Feature Pyramid Network for Object Detection
https://github.com/Beaver48/kaggle-chest-xray-abnormalities
https://github.com/BebDong/MXNetSeg
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/Ben-Louis/FisherPruning-Pytorch
https://github.com/BenjaminBradshaw/Fast-Style-Transfer-for-Arbitrary-Styles
Exploring the structure of a real-time, arbitrary neural artistic stylization network
https://github.com/BenjaminLiuPenrose/UnsupervisedImage
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
https://github.com/BenjiKCF/EfficientNet
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/BenjiKCF/Superesolution-and-watermark-removal
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Bennie-Han/Image-augementation-pytorch
Training Region-based Object Detectors with Online Hard Example Mining
https://github.com/Benzlxs/benzlxs.github.io
Three-dimensional Backbone Network for 3D Object Detection in Traffic Scenes
https://github.com/BerkeleyLearnVerify/VerifAI
https://github.com/BertaBescos/DynaSLAM
DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes
https://github.com/Biantian/MscProject
https://github.com/Bigpingping97/ICNet
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
https://github.com/Bigwode/rebar-detection-competition
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.