https://github.com/alibaba/EasyCV
Circle Loss: A Unified Perspective of Pair Similarity Optimization
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/alililia/ascend_ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/alililia/ascend_HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/alililia/ascend_sphereface
https://github.com/alililia/gpu_sphereface
https://github.com/alililia/ms_extend/tree/main/gpu_retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/alinlab/LfF
Learning from Failure: Training Debiased Classifier from Biased Classifier
https://github.com/aliprf/Ad-Corre
https://github.com/alldbi/Factorized-Spatial-Embeddings
Unsupervised learning of object landmarks by factorized spatial embeddings
https://github.com/allenai/satlas-super-resolution
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/alsgkals2/CoReD_Released
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation
https://github.com/alsgkals2/cored
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation
https://github.com/altndrr/persona
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/altomator/Introduction_to_Deep_Learning-2-Face_Detection
https://github.com/alvinwan/shiftresnet-cifar
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
https://github.com/aman-arya/Any-Body-Can-Dance
https://github.com/amanshenoy/pose-invariant-face-recognition
https://github.com/aminekha/AI-For-2022
https://github.com/amirhfarzaneh/dacl
https://github.com/amittiwary42/target-detection-eeg-signals
https://github.com/amogh7joshi/media-vision
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/anax32/dimensionality-reduction
https://github.com/andreas128/NTIRE21_Learning_SR_Space
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution
https://github.com/andrire/RNNASIP-pulpissimo
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
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/aniket03/keras_compact_bilnear_CNN
https://github.com/anirudharc/transformer
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/annabellachen/newDarknet
https://github.com/anookeen/yolo
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.