https://github.com/mlpc-ucsd/PRTR
Deep High-Resolution Representation Learning for Visual Recognition
Papers with Code 아카이브
3D Face Reconstruction
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3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mlpocprojects/facenet-poc
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mlu355/MetadataNorm
Representation Learning with Statistical Independence to Mitigate Bias
https://github.com/mlvccn/bmtc_transferattackvid
https://github.com/mlvlab/dapt
https://github.com/mminamina/Transfer_Learning_NaimishNet---Keypoints_Detection
https://github.com/mminamina/Transfer_Learning_ResNet18---Keypoints_Detection
https://github.com/mnguyen0226/image-augmentation-dnn-performance
https://github.com/mnikitin/Learn-Convolutional-Neural-Network-for-Face-Anti-Spoofing
https://github.com/moado/expression_recognition
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/moallafatma/Breast_Cancer_Detection_Classification
https://github.com/mobilesec/arcface-tensorflowlite
https://github.com/moddy2024/resnet-9
https://github.com/modelhub-ai/arc-face
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/modelhub-ai/emotion-fer-plus
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
https://github.com/modelhub-ai/network-in-network
https://github.com/modelhub-ai/vgg-19
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/modestyachts/ImageNetV2
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mohaEs/Train-Predict-Landmarks-by-flat-net
Automatic vocal tract landmark localization from midsagittal MRI data
https://github.com/mohamedameen93/German-Traffic-Sign-Classification-Using-TensorFlow
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mohammadimathstar/grlgq
https://github.com/mohanliu/HRnet-semantic-segmentation-exp
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/mohitwildbeast/Facial-Recognition-Using-FaceNet-Siamese-One-Shot-Learning
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/moron96/FaceRecogLDAP
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mortezagolzan/Face-Anti-Spoofing
https://github.com/mosmos/face_key_point_detection
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/mowshon/lipsync
A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild
https://github.com/mr-bulb/DL_basic_github
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mrpintime/Face-Liveness-TensorFlow
Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
https://github.com/mrv8x/DeepFaceLab
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/mrw-soumik/Tiny-Faces-in-Tensorflow
https://github.com/mrzzy/np-dl-assign-1
https://github.com/msaadsaeed/sbnet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mseg-dataset/mseg-semantic
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/mshehrozsajjad/Age-Classification
Rank consistent ordinal regression for neural networks with application to age estimation
https://github.com/mszpc/facenet_ascend
FaceNet: A Unified Embedding for Face Recognition and Clustering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.