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/ThrupthiAnn/ThrupthiAnn.github.io
https://github.com/TieDanCuihua/A-STRUCTURED-SELF-ATTENTIVE-SENTENCE-EMBEDDING
https://github.com/TimoBolkart/BFM_to_FLAME
https://github.com/TimoBolkart/FLAME-Blender-Add-on
https://github.com/TimoBolkart/FLAME-Universe
https://github.com/TimoBolkart/TF_FLAME
https://github.com/TinDang97/face_recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/TinyZeaMays/CircleLoss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/TotoHugo/facedetection-lite-Outsystems
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/TowardHumanizedInteraction/TripletFace
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Traffic-X/Open-TransMind
https://github.com/TreB1eN/InsightFace_Pytorch
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
https://github.com/TropComplique/FaceBoxes-tensorflow
https://github.com/TropComplique/mtcnn-pytorch
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/Trustworthy-AI-Group/TransferAttack
Improving the Transferability of Targeted Adversarial Examples through Object-Based Diverse Input
https://github.com/TsingZ0/PFL-Non-IID
Federated Learning for Face Recognition with Gradient Correction
https://github.com/UnrealLink/TP-GAN
https://github.com/Unturned3/mtcnn
https://github.com/VedantDere0104/Progressive_Growing_of_GANs
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/VedantDere0104/StyleGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/VigneshS10/Segmentation-VGG19
https://github.com/Vill-Lab/2023-TIFS-DTIBA
FastReID: A Pytorch Toolbox for General Instance Re-identification
https://github.com/Vill-Lab/2024-TIP-MetaPrompt
https://github.com/Vishal-V/GSoC-TensorFlow-2019/blob/master/face_app/model.py
https://github.com/VisiumCH/AMLD2020-Dirty-Gancing
https://github.com/ViswanathaReddyGajjala/EfficientNet-RetinaNet
https://github.com/Viveksbawa/SARAS-ESAD-Baseline
https://github.com/VladAndronik/face_swap
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/WangChen0902/MTCNN-Paddle
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/WangChen0902/RetinaFace-Paddle
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/Wangxy2180/darknetKinectDetect
https://github.com/Wastoon/TSAL
Teacher-Student Asynchronous Learning with Multi-Source Consistency for Facial Landmark Detection
https://github.com/WeiHongLee/Learning-to-impute
Learning to Impute: A General Framework for Semi-supervised Learning
https://github.com/WeidiXie/Keras-VGGFace2-ResNet50
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/Weijian-li/unsupervised_inter_intra_landmark
Structured Landmark Detection via Topology-Adapting Deep Graph Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.