https://github.com/18alantom/smel_project
FaceNet: A Unified Embedding for Face Recognition and Clustering
Papers with Code 아카이브
Face Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 25
- 보존된 평가 기록
- 88
Facial Recognition is the task of making a positive identification of a face in a photo or video image against a pre-existing database of faces. It begins with detection - distinguishing human faces from other objects in the image - and then works on identification of those detected faces.
The state of the art tables for this task are contained mainly in the consistent parts of the task : the face verification and face identification tasks.
<span style="color:grey; opacity: 0.6">( Image credit: Face Verification )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/1996scarlet/ArcFace-Multiplex-Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/1ho0jin1/QMUL-SurvFace-Open-Set-Identification
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/LightCNN
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/MaskedFaceRecognition
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/DeepID
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FaceNet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/RetinaFace_ResNet50
Video Face Recognition System: RetinaFace-mnet-faster and Secondary Search
https://github.com/2023-MindSpore-4/Code-5/tree/main/LightCNN
https://github.com/2023-MindSpore-4/Code-5/tree/main/MaskedFaceRecognition
https://github.com/2023-MindSpore-4/Code1/tree/main/Arcface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/2023-MindSpore-4/Code10/tree/main/Arcface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/2023-MindSpore-4/Code11/tree/main/retinaface
Video Face Recognition System: RetinaFace-mnet-faster and Secondary Search
https://github.com/2023-MindSpore-4/Code11/tree/main/sphereface
https://github.com/2023-MindSpore-4/Code2/tree/main/DeepID
https://github.com/2023-MindSpore-4/Code7/tree/main/STPM
Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
https://github.com/2023-MindSpore-4/Code7/tree/main/sphereface
https://github.com/2023-MindSpore-4/Code7/tree/main/squeezenet
https://github.com/2023-MindSpore-4/Code8/tree/main/cdp
Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition
https://github.com/2024-MindSpore-1/Code4/tree/main/Arcface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/2024-MindSpore-1/Code4/tree/main/RetinaFace_ResNet50
Video Face Recognition System: RetinaFace-mnet-faster and Secondary Search
https://github.com/2024-MindSpore-1/Code5/tree/main/AlignedReID
Domain adaptation for person re-identification on new unlabeled data using AlignedReID++
https://github.com/2024-MindSpore-1/Code7/tree/main/cdp
Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition
https://github.com/394781865/insightface
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
https://github.com/3P2S/arcface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/4uiiurz1/pytorch-adacos
AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations
https://github.com/AbdallahMGomaa/PatchNet
PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition
https://github.com/Abdelhamid-bouzid/Deep-metric-learning
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/AbdielNie/GAN_Face-Rotation
https://github.com/Adarsh79/Face-Recognition-with-Facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/AdrianUng/keras-triplet-loss-mnist
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Agrover112/SiameseNet-Search
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Alireza-Akhavan/face-quality-metrics
FaceQnet: Quality Assessment for Face Recognition based on Deep Learning
https://github.com/AmirSh15/FECNet
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/AmrTarekk/Attendence-system-using-Facial-Recognition-
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Ander02/FaceRecognition
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.