https://github.com/andersoncarlosfs/image_classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
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/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.