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/v-trungdt21/MaskTheFace
https://github.com/valentingol/GANJax
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/vantupham/darknet
https://github.com/varennes/deep-autoencoder
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/varshaneya/Res-SE-Net
https://github.com/varununleashed/tiny_faces_temp
https://github.com/vayuvegula/kerasModels
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vbonifaci/l1opt
https://github.com/vendyv/CodeSpeedy_Internship
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vgangal101/VGG_models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vgangal101/resnet_models
https://github.com/vicksam/fer-model
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
https://github.com/victespinoza/NeuralStyleTransfer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/viebboy/MultilinearCompressiveLearningWithPrior
https://github.com/vietanhdev/open-adas
https://github.com/vietdhoang/resnet-18
https://github.com/viethungluu/OCRetina
https://github.com/vijishmadhavan/SkinDeep
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/vikramkarthikeyan/Face-R-FCN
Detecting Faces Using Region-based Fully Convolutional Networks
https://github.com/vill-lab/2024-aaai-hpt
https://github.com/vinairesearch/lemul
https://github.com/vinay-EIP/EIP-session-5-assignment
https://github.com/vinayakkailas/Face_Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/vincent-thevenin/Realistic-Neural-Talking-Head-Models
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
https://github.com/vincenthanna/facenet_on_mnist
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/vineeths96/Gradient-Compression
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vineeths96/heterogeneous-systems
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vinod377/STN-OCR
https://github.com/vinod377/STN-OCR-Tensorflow
https://github.com/vinx-2105/madgan-degan
https://github.com/vipermu/ganimation
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/visionNoob/hrnet_pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/vita-epfl/rock-pytorch
https://github.com/vitoralbiero/face_analysis_pytorch
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/vladimirwest/insightface_cinematic
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.