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/OFRIN/Tensorflow_GIoU

Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression

https://github.com/OFRIN/Tensorflow_RetinaFace

Focal Loss for Dense Object Detection

https://github.com/OFRIN/Tensorflow_YOLOv1

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

https://github.com/OIPLab-DUT/CVPR2020-A2dele

https://github.com/OIPLab-DUT/CVPR_SSF-RGBD

https://github.com/OML-Team/open-metric-learning

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/OceanPang/Libra_R-CNN

Libra R-CNN: Towards Balanced Learning for Object Detection

https://github.com/Octavio-Pappalardo/MAML_for_RL_pytorch

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/OfekCohen1/Style-On-3D-Video

Artistic style transfer for videos and spherical images

https://github.com/Ohyeon5/MismatchPenaltySegmentation

SSD: Single Shot MultiBox Detector

https://github.com/Ohyeon5/MultiscaleSegmentation

SSD: Single Shot MultiBox Detector

https://github.com/Oichii/DeepPulse-pytorch

GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

https://github.com/Okery/PyTorch-Simple-MaskRCNN

Mask R-CNN

https://github.com/OlafenwaMoses/Action-Net

Deep Residual Learning for Image Recognition

https://github.com/OlafenwaMoses/FireNET

YOLOv3: An Incremental Improvement

https://github.com/OlafenwaMoses/IdenProf

Deep Residual Learning for Image Recognition

https://github.com/OlafenwaMoses/Traffic-Net

Deep Residual Learning for Image Recognition

https://github.com/Olayemiy/Image-Classification-With-Resnet

Deep Residual Learning for Image Recognition

https://github.com/OlgaFomin/Speech-enhancement

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/OliverJBoom/Histopathologic-Cancer-Detection

Squeeze-and-Excitation Networks

https://github.com/Omar-Awad/SCNN_GPU2

SBNet: Sparse Blocks Network for Fast Inference

https://github.com/Omkar-Ranadive/Domain-Adaptation-CycleGAN

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

https://github.com/One-sixth/gan-qp-mod-pytorch

GAN-QP: A Novel GAN Framework without Gradient Vanishing and Lipschitz Constraint

https://github.com/OniroAI/Instance-segmentation-with-MobileNetV3

Searching for MobileNetV3

https://github.com/OpenAOI/anodet

Towards Total Recall in Industrial Anomaly Detection

https://github.com/OpenCv30/Yolov3

YOLOv3: An Incremental Improvement

https://github.com/OpenFirework/pytorch_solov2

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/OpenSpaceAI/DEST3D

State Space Model Meets Transformer: A New Paradigm for 3D Object Detection

https://github.com/OpenSpaceAI/TI-Face

TIFace: Improving Facial Reconstruction through Tensorial Radiance Fields and Implicit Surfaces

https://github.com/OscarPellicer/prostate_lesion_detection

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

https://github.com/Osdel/ssnets

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Our4514/CAGFUZZ

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

https://github.com/Oussamayousre/Yoga_pose_recognizer

Feature Pyramid Networks for Object Detection

https://github.com/Owais-Ansari/Unet3plus

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/OwlTing/AI_basketball_games_video_editor

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/P2333/Max-Mahalanobis-Training

Towards Deep Learning Models Resistant to Adversarial Attacks

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