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/heathentw/prnet-tf2
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
https://github.com/hectorgie/DeepFaceLab
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/hemanshanand/Facial-Expression-Recognition
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/henriquemeloo/cat-dog-image-classifier
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/heorhii-bolotov/facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/hershd23/ObjectLocalizer
https://github.com/hggym/pigo
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/hh-xiaohu/Image-augementation-pytorch
Training Region-based Object Detectors with Online Hard Example Mining
https://github.com/hhenryd/tap
https://github.com/hhj1897/face_detection
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/hhuaibo/darknet
https://github.com/hieu2906090/deep-learning-in-js
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/hisiter97/darknet
https://github.com/hnVfly/pointnet.mxnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/hnmspirit/pointnet1
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/hollance/BlazeFace-PyTorch
BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
https://github.com/hollance/VGGNet-Metal
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/holman57/AI_Emotion_Detection
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
https://github.com/holstgr-kaust/keras-tutorials
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/hongkunsun/paratranscnn
https://github.com/hongyi-zhang/Fixup
https://github.com/horizontel/aigibench
Generalizable Deepfake Detection via Effective Local-Global Feature Extraction
https://github.com/horse007666/ResNet
https://github.com/hqhoangvuong/paperspace_ml_01
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/hqli/face_recognition
https://github.com/hqng/imm-pytorch
Unsupervised Learning of Object Landmarks through Conditional Image Generation
https://github.com/hsd1503/resnet1d
https://github.com/hsinyilin19/resnetvae
https://github.com/hslrock/TripletLoss_Pytorch
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/huangshenneng/padd_retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/huashen218/multiturncleanup
Does Human Collaboration Enhance the Accuracy of Identifying LLM-Generated Deepfake Texts?
https://github.com/huawenwei4/dfl
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/hubert0527/COCO-GAN
https://github.com/hui-po-wang/hijackgan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/hukangli/https-github.com-deepinsight-insightface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.