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/yuvrajarora/CSCI5922_Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/yuxiangalvin/DeepLOB-Model-Implementation-Project
https://github.com/yuzq97/starter_project
Interpreting the Latent Space of GANs for Semantic Face Editing
https://github.com/yw0nam/DenseNet
https://github.com/yxgeee/MMT
https://github.com/yxlijun/s3fd.pytorch
https://github.com/yxu0611/tensorflow-implementation-of-lcnn
https://github.com/yyfsXZ/structured_self_attention_sent_embedding
https://github.com/yyk-wew/F3Net
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/yytang2012/darknet
https://github.com/yzhou359/MakeItTalk
https://github.com/yzyouzhang/AIR-ASVspoof
UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
https://github.com/zachzhu2016/Spectraface
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/zachzhu2016/thermal-face-recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/zafartakekh/finddrop
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/zengqunzhao/efficientface
https://github.com/zengqunzhao/ma-net
https://github.com/zenonLEE/MDFLD
Towards Multi-domain Face Landmark Detection with Synthetic Data from Diffusion model
https://github.com/zero-or-one/URP
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
https://github.com/zexUlt/facerec
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/zgx0534/pointnet_win
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/zhangbo2008/best_pytorch_transformer
https://github.com/zhaoxin111/insightface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/zhen8838/Circle-Loss
https://github.com/zheng-ningxin/Pruning-from-scratch
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/zheng1weiyu/Insightface_for_FaceRecog
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/zhixinshu/DeformingAutoencoders-pytorch
Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance
https://github.com/zhongzisha/object_detection
https://github.com/zhuccly/glomface-face-alignment
https://github.com/zhuccly/saat
https://github.com/zhusz/CVPR15-CFSS
https://github.com/zineos/blazeface
BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
https://github.com/zisianw/FaceBoxes.PyTorch
https://github.com/zj463261929/darknet_mAP
https://github.com/zjZSTU/ResNet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.