https://github.com/jung-jun-uk/mixface
공식 코드MixFace: Improving Face Verification Focusing on Fine-grained Conditions
Papers with Code 아카이브
Facial Recognition and Modelling
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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/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/jungyu0413/Navigating-Label-Ambiguity-NLA-
공식 코드Navigating Label Ambiguity for Facial Expression Recognition in the Wild
https://github.com/jungyu0413/V-NAW
공식 코드V-NAW: Video-based Noise-aware Adaptive Weighting for Facial Expression Recognition
https://github.com/junjun-jiang/Face-Hallucination-Benchmark
공식 코드https://github.com/junjun-jiang/TLcR-RL
공식 코드https://github.com/junshutang/3DFaceShop
공식 코드3DFaceShop: Explicitly Controllable 3D-Aware Portrait Generation
https://github.com/junwan2014/MMDN-master
공식 코드Robust Facial Landmark Detection by Multi-order Multi-constraint Deep Networks
https://github.com/justusschock/shapenet
공식 코드https://github.com/jymoon0613/simfle
공식 코드https://github.com/kaiwang960112/Challenge-condition-FER-dataset
공식 코드Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition
https://github.com/kaiwang960112/Self-Cure-Network
공식 코드Suppressing Uncertainties for Large-Scale Facial Expression Recognition
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/kunkunlin1221/InstructFLIP
공식 코드InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing
https://github.com/kwanyun/FFaceNeRF
공식 코드https://github.com/kwanyun/LeGO_code
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.