https://github.com/andersoncarlosfs/image_classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/andreas128/NTIRE21_Learning_SR_Space
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution
https://github.com/andreasveit/densenet-pytorch
https://github.com/andrijdavid/clinical-brain-interface-2020
https://github.com/andrire/RNNASIP-pulpissimo
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
https://github.com/angelvillar96/FaceEmoji
https://github.com/anguyen8/sam
https://github.com/anhttran/3dmm_basic
Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
https://github.com/anhttran/3dmm_cnn
Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
https://github.com/anhtu293/Vietnamese-Celebrity-Face-Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/anibali/dsnt-pose2d
https://github.com/aniket-patra-1998/FLOWER_RECOGNITION
https://github.com/aniket03/keras_compact_bilnear_CNN
https://github.com/anirudharc/transformer
https://github.com/anitagold/30-days-of-Udacity
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/anjandeepsahni/face_classification
https://github.com/anjandeepsahni/face_recognition
https://github.com/anjith2006/bob.paper.mcae.icb2019
Domain Adaptation in Multi-Channel Autoencoder based Features for Robust Face Anti-Spoofing
https://github.com/anjith2006/bob.paper.mccnn.tifs2018
Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network
https://github.com/anjith2006/bob.paper.oneclass_mccnn_2019
https://github.com/anjith2006/bob.paper.tbiom2023_edgeface
https://github.com/anjith2006/bob.paper.tifs2022_hfr_prepended_domain_transformer
Prepended Domain Transformer: Heterogeneous Face Recognition without Bells and Whistles
https://github.com/ankit-vaghela30/Google-landmark-prediction
https://github.com/annabellachen/newDarknet
https://github.com/anookeen/yolo
https://github.com/anoushkrit/Knowledge
https://github.com/anshky/HR-NET
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/anshu123priya/Real-v-s-Fake-Emotion-Challenge
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/anshu123priya/Real-vs-Fake-Emotion-Challenge
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/anuj-anuj/face-similarity
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/anujdutt9/Artistic-Style-Transfer-using-Keras-Tensorflow
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/aobaruwa/TensorFlow-Projects
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/aoru45/BasketNet
https://github.com/aoru45/Deep-Anomaly-Detection-for-Generalized-Face-Anti-Spoofing
https://github.com/aoru45/LFFD-Pytorch
https://github.com/apaz-cli/ML-ImageHash
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.