Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/zhao-zilong/MotivationCaseStudies
공식 코드Enhancing Robustness of On-line Learning Models on Highly Noisy Data
https://github.com/zhaoweicai/mscnn
공식 코드A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection
https://github.com/zhaoyuzhi/childpredictor
공식 코드ChildPredictor: A Child Face Prediction Framework with Disentangled Learning
https://github.com/zhelishisongjie/ssfer
공식 코드https://github.com/zhenglab/ffdbackbone
공식 코드https://github.com/zhenglinzhou/star
공식 코드STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection
https://github.com/zhenglisec/decision-based-mia
공식 코드https://github.com/zhenglisec/unganable
공식 코드https://github.com/zhengqinlai/imer-benchmark
공식 코드https://github.com/zhichaowang970201/text-to-video
공식 코드Text-to-Video: a Two-stage Framework for Zero-shot Identity-agnostic Talking-head Generation
https://github.com/zhihengli-UR/DebiAN
공식 코드Discover and Mitigate Unknown Biases with Debiasing Alternate Networks
https://github.com/zhipeixu/fakeshield
공식 코드https://github.com/zhiqiangdon/CU-Net
공식 코드Quantized Densely Connected U-Nets for Efficient Landmark Localization
https://github.com/zhiqic/keyposs
공식 코드KeyPosS: Plug-and-Play Facial Landmark Detection through GPS-Inspired True-Range Multilateration
https://github.com/zhiwenshao/ac2d
공식 코드https://github.com/zhongyy/Adversarial_MTER
공식 코드Adversarial Learning with Margin-based Triplet Embedding Regularization
https://github.com/zhongyy/Face-Transformer
공식 코드https://github.com/zhongyy/SFace
공식 코드SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
https://github.com/zhongyy/opom
공식 코드OPOM: Customized Invisible Cloak towards Face Privacy Protection
https://github.com/zhu00121/universal-representation-dynamics-of-deepfake-speech
공식 코드https://github.com/zhuccly/srn
공식 코드Reasoning Structural Relation for Occlusion-Robust Facial Landmark Localization
https://github.com/zhuhao-nju/describe3d
공식 코드High-Fidelity 3D Face Generation from Natural Language Descriptions
https://github.com/zhuhao-nju/facescape
공식 코드FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction
https://github.com/zhuhao-nju/rafare
공식 코드RAFaRe: Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs
https://github.com/zimzsh/cross-corpus-readability-compatibility-assessment-for-english-texts
공식 코드Cross-corpus Readability Compatibility Assessment for English Texts
https://github.com/ziqiao-shang/aunce
공식 코드Learning Contrastive Feature Representations for Facial Action Unit Detection
https://github.com/ziqihuangg/collaborative-diffusion
공식 코드Collaborative Diffusion for Multi-Modal Face Generation and Editing
https://github.com/zitongyu/flex-modal-fas
공식 코드https://github.com/zju-pi/awesome-diffusion-generated-image-detection
공식 코드Recent Advances on Generalizable Diffusion-generated Image Detection
https://github.com/zma-c-137/VarGFaceNet
공식 코드https://github.com/zoukaifeng/4dfm
공식 코드https://github.com/zouxinyi0625/cdnet
공식 코드https://github.com/zpguigroupwhu/meancut-clustering
공식 코드MeanCut: A Greedy-Optimized Graph Clustering via Path-based Similarity and Degree Descent Criterion
https://github.com/zqbai-jeremy/INORig
공식 코드https://github.com/zwx8981/adth-qa
공식 코드A Comparative Study of Perceptual Quality Metrics for Audio-driven Talking Head Videos
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.