Papers with Code 아카이브
3D Face Reconstruction
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3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ThomasWangY/2024-AAAI-HPT
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/Tools4Project/4501Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
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/UKPLab/coling18-multimodalSurvey
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/UnofficialJuliaMirror/DeepMark-deepmark
https://github.com/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark
https://github.com/UnrealLink/TP-GAN
https://github.com/Unturned3/mtcnn
https://github.com/VaanHUANG/CSCI5210HW1
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/Vakihito/SentimentYoutube
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Vamshi399/CarND-Vehicle-Detection
https://github.com/VamsiKrishna1211/gender_age-detection
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/VhalPurohit/290s
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/VinayBN8997/ResNet-CIFAR10
https://github.com/Vishal-V/GSoC-TensorFlow-2019/blob/master/face_app/model.py
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.