Papers with Code 아카이브
Face Reconstruction
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Face reconstruction is the task of recovering the facial geometry of a face from an image.
<span style="color:grey; opacity: 0.6">( Image credit: Microsoft Deep3DFaceReconstruction )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/LuigiRussoDev/Covid19Detection
https://github.com/LuigiRussoDev/ResNets
https://github.com/Lw510107/pointnet-2018.6.27-
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/M155K4R4/facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/MFajcik/RumourEval2019
https://github.com/MIC-DKFZ/DetectionAndRegression
https://github.com/MIC-DKFZ/RegRCNN
https://github.com/MNaplesDevelopment/DCGAN-PyTorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MNaplesDevelopment/Deep-Convolutional-Generative-Adversarial-Networks
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MNaplesDevelopment/MNIST-DCGAN-PyTorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MS-Mind/MS-Code-02/tree/main/configs/mixnet
https://github.com/MS-Mind/MS-Code-02/tree/main/configs/resnet
https://github.com/MS-Mind/MS-Code-06/tree/main/PGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MalayAgarwal-Lee/MesoNet-DeepFakeDetection
https://github.com/MaliParag/ScanSSD
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Maninder10/face
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/ManyiLee/Open-world-Deepfake-Detection-Network
ODDN: Addressing Unpaired Data Challenges in Open-World Deepfake Detection on Online Social Networks
https://github.com/MariefW/6.-trainingYOLO
https://github.com/MarkHershey/arxiv-dl
https://github.com/Martion-z/Paddle-PULSE
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/Martion-z/pytorch-Pulse
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/Masao-Taketani/FOTS_OCR
https://github.com/Maskify/darknet
https://github.com/MatGod7/Retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/MathiasStensrud/autoBleep
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Maveric4/pr19aaw01
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/MaxLikesMath/DeepLearningImplementations
DeXpression: Deep Convolutional Neural Network for Expression Recognition
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Network_In_Network
https://github.com/MaximilianHollis/Maskify
BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
https://github.com/MaxwellHeller/coffee_fraud_detection
https://github.com/Mayurji/Image-Classification-PyTorch
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/MegEngine/Models/tree/master/official/vision/classification/resnet
https://github.com/MegEngine/Models/tree/master/official/vision/detection
https://github.com/Meghraj-Webllisto/stylegan
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Melo-Wang/Deep-Learning-on-Point-Cloud-of-Aerospace-Components-for-3D-Classification
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.