https://github.com/jingyang2017/srd_ossl
공식 코드Knowledge Distillation Meets Open-Set Semi-Supervised Learning
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/jinyugy21/adv-stickers_rhde
공식 코드Adversarial Sticker: A Stealthy Attack Method in the Physical World
https://github.com/jkwang28/osdface
공식 코드https://github.com/joelb92/ND_Frontalization_Project
공식 코드https://github.com/jongli747/curricular-sincnet
공식 코드https://github.com/josephdrahos/sreds
공식 코드https://github.com/jung-jun-uk/mixface
공식 코드MixFace: Improving Face Verification Focusing on Fine-grained Conditions
https://github.com/jung-jun-uk/unpg
공식 코드Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition
https://github.com/jungyg/alsuv
공식 코드Face Reconstruction Transfer Attack as Out-of-Distribution Generalization
https://github.com/keivanB/Young_Face_Aging_YFA
공식 코드https://github.com/kgrm/face-recog-eval
공식 코드Strengths and Weaknesses of Deep Learning Models for Face Recognition Against Image Degradations
https://github.com/khalilimahdi/loss_balancing_icml2023
공식 코드https://github.com/khawar-islam/fpvt
공식 코드https://github.com/kim1102/IG-FIQA
공식 코드https://github.com/kim1102/VIGFace
공식 코드VIGFace: Virtual Identity Generation for Privacy-Free Face Recognition
https://github.com/kjanjua26/Git-Loss-For-Deep-Face-Recognition
공식 코드https://github.com/kk7nc/RMDL
공식 코드https://github.com/kkkcx/diffender
공식 코드DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks
https://github.com/koushiksrivats/flip
공식 코드FLIP: Cross-domain Face Anti-spoofing with Language Guidance
https://github.com/langlrsw/AAL-unbiased-authentication
공식 코드https://github.com/leebebeto/inter-prototype
공식 코드Improving Face Recognition with Large Age Gaps by Learning to Distinguish Children
https://github.com/lehinevych/SAAN
공식 코드Self-attention aggregation network for video face representation and recognition
https://github.com/lexieyang/face_img_inpainting
공식 코드https://github.com/li-8023/multi-function-face-recognition
공식 코드https://github.com/ligaripash/facecoresetnet
공식 코드FaceCoresetNet: Differentiable Coresets for Face Set Recognition
https://github.com/lingxiao-he/Partial-Person-ReID
공식 코드https://github.com/liuyuisanai/trojans-face-recognizer
공식 코드https://github.com/liuyvchi/NROLL
공식 코드Boosting Semi-Supervised Face Recognition with Noise Robustness
https://github.com/lizhaoliu-Lec/DAS
공식 코드https://github.com/lmbxmu/EPruner
공식 코드https://github.com/longph1989/Socrates
공식 코드SOCRATES: Towards a Unified Platform for Neural Network Analysis
https://github.com/lsibabnikz/ai-kd
공식 코드AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge Distillation
https://github.com/lsibabnikz/faceqan
공식 코드FaceQAN: Face Image Quality Assessment Through Adversarial Noise Exploration
https://github.com/lsibabnikz/optimization-based-improvement-of-fiqa-techniques
공식 코드Optimization-Based Improvement of Face Image Quality Assessment Techniques
https://github.com/luisrui/seeing-ai-system
공식 코드https://github.com/lukasstruppek/class_attribute_inference_attacks
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.