https://github.com/kaiwang960112/Self-Cure-Network
공식 코드Suppressing Uncertainties for Large-Scale Facial Expression Recognition
Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 25
- 평가표
- 0
- 보존된 평가 기록
- 0
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/kaiyangzhou/coop
공식 코드https://github.com/kalyo-zjl/WM3DR
공식 코드https://github.com/kangyeolk/animeceleb
공식 코드AnimeCeleb: Large-Scale Animation CelebHeads Dataset for Head Reenactment
https://github.com/kartik-3004/segface
공식 코드https://github.com/kdhht2334/elim_fer
공식 코드Optimal Transport-based Identity Matching for Identity-invariant Facial Expression Recognition
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/khurramHashmi/FeatEnHancer
공식 코드FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision
https://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/konstantinkobs/SimLoss
공식 코드https://github.com/koushiksrivats/flip
공식 코드FLIP: Cross-domain Face Anti-spoofing with Language Guidance
https://github.com/krasjet-yu/yolo-facev2
공식 코드https://github.com/ksasi/fairDL
공식 코드https://github.com/kuhnkeF/ABAW2020TNT
공식 코드https://github.com/kwanyun/FFaceNeRF
공식 코드https://github.com/kwanyun/LeGO_code
공식 코드https://github.com/kwanyun/StyleSketch
공식 코드Stylized Face Sketch Extraction via Generative Prior with Limited Data
https://github.com/l8cv/busterx
공식 코드BusterX: MLLM-Powered AI-Generated Video Forgery Detection and Explanation
https://github.com/laiyingxin2/dadf
공식 코드Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization
https://github.com/laiyingxin2/gm-df
공식 코드https://github.com/lalithbharadwajbaru/wavelet-clip
공식 코드Wavelet-Driven Generalizable Framework for Deepfake Face Forgery Detection
https://github.com/langlrsw/AAL-unbiased-authentication
공식 코드https://github.com/lattas/avatarme
공식 코드AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
https://github.com/leaffeall/DFS-GDD
공식 코드Decoupling Forgery Semantics for Generalizable Deepfake Detection
https://github.com/learninginvision/spu
공식 코드Self-Paced Deep Regression Forests with Consideration of Ranking Fairness
https://github.com/leebebeto/inter-prototype
공식 코드Improving Face Recognition with Large Age Gaps by Learning to Distinguish Children
https://github.com/leeisack/latent-ofer
공식 코드https://github.com/lehinevych/SAAN
공식 코드Self-attention aggregation network for video face representation and recognition
https://github.com/lelechen63/Talking-head-Generation-with-Rhythmic-Head-Motion
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.