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/dataflowr/self-attentive-sentence-embedding
https://github.com/datawiz1984/MLND_Capstone_Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datawiz1984/malaria-model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datoboat/Vehicle-Detection
https://github.com/daveboat/pytorch_focal_loss
https://github.com/davisking/dlib
https://github.com/dc17540/darknet
https://github.com/dchen236/FairFace
FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age
https://github.com/dead-mazai/avia-missing-airplanes
https://github.com/debajyotid2/pointnet_pl
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/decile-team/cords
https://github.com/deepakks1995/inception
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/deepfakes/faceswap
DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection
https://github.com/deepinx/SDU_face_alignment
Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment
https://github.com/deepinx/ShuffleNet_v1_and_v2
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/deepinx/iqiyi-vid-challenge
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/deepinx/sdu-face-alignment
Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment
https://github.com/deepinx/shufflenet-v1-and-v2
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/deeplearning987/DoodleClassifier
https://github.com/deeplearningnapratica/pulse
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/deepmind/dm-haiku
https://github.com/deepmodeling/deepmd-kit
https://github.com/deepquestai/fire-smoke-dataset
https://github.com/deftruth/torchlm
Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild
https://github.com/delmalih/MIAS-mammography-obj-detection
https://github.com/demul/ResidualNet
https://github.com/dengpingfan/fsgan
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/denis19973/faceshifter_tornado
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/deontaepharr/Residual-Attention-Network
https://github.com/derek-baker/group3
Spotting Macro- and Micro-expression Intervals in Long Video Sequences
https://github.com/detectionteamucas/retinanet_tensorflow
https://github.com/dhaalves/CEAL_keras
Cost-Effective Active Learning for Deep Image Classification
https://github.com/dheerajsingh7351/facedetect
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/dhesenkamp/attentive-lstm
https://github.com/didi/AoE
SeesawFaceNets: sparse and robust face verification model for mobile platform
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.