https://github.com/fdbtrs/QuantFace
공식 코드QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit Quantization
Papers with Code 아카이브
Lightweight Face Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 7
- 보존된 평가 기록
- 27
Lightweight Face Recognition models are a group of face recognition models with lightweight backbones, which can be used for mobile or edge device applications.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/fdbtrs/mixfacenets
공식 코드https://github.com/fdbtrs/pocketnet
공식 코드https://github.com/liuyuisanai/trojans-face-recognizer
공식 코드https://github.com/otroshi/edgeface
공식 코드https://github.com/otroshi/synthdistill
공식 코드SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data
https://github.com/zma-c-137/VarGFaceNet
공식 코드https://gitlab.idiap.ch/bob/bob.paper.ijcb2023_synthdistill
공식 코드SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data
https://github.com/394781865/insightface
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/KikimorMay/MultiFace
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
SeesawFaceNets: sparse and robust face verification model for mobile platform
https://github.com/TreB1eN/InsightFace_Pytorch
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/agrawalparth10/Face-is-the-Key
https://github.com/anjith2006/bob.paper.tbiom2023_edgeface
https://github.com/chenggongliang/arcface
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/cvtower/SeesawNet-pytorch-reimplement
SeesawFaceNets: sparse and robust face verification model for mobile platform
https://github.com/cvtower/SeesawNet_pytorch
SeesawFaceNets: sparse and robust face verification model for mobile platform
https://github.com/cvtower/seesawfacenet_pytorch
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/david-svitov/margindistillation
ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student Networks
https://github.com/deepinsight/insightface
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/deepinx/ShuffleNet_v1_and_v2
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/deepinx/shufflenet-v1-and-v2
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/didi/AoE
SeesawFaceNets: sparse and robust face verification model for mobile platform
https://github.com/eric-erki/insightface
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/foamliu/MobileFaceNet
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/godofpdog/MobileFaceNet_keras
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/patrick-batman/Angular-Knowledge-Distillation
ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student Networks
https://github.com/pshashk/seesaw-facenet
SeesawFaceNets: sparse and robust face verification model for mobile platform
https://github.com/qidiso/mobilefacenet-V2
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/sunil-rival/insightface
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/w510056105/DeepLearning
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/xiaoccer/mobilefacenet_pytorch
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/yule-li/MassFace
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/zrui94/insight_mx
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://gitlab.idiap.ch/bob/bob.paper.tbiom2023_edgeface
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.