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/johngear/eecs504
https://github.com/johnnylu305/resnet-50-101-152
https://github.com/jolibrain/caffe
https://github.com/jonasz/progressive_infogan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/jonathandrnd/Face-Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/jonathangiguere/Emotion_Image_Classifier
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild
https://github.com/joonson/yousaidthat
https://github.com/joovvhan/ecapa-tdnn
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/jooyae/NVIDIA_STYLEGAN
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/jooyounghun/AI-Team-5
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/jordan-bird/synthetic-fruit-image-generator
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/jtcass01/SIMON
https://github.com/jtchen0528/PCL-I2G
https://github.com/jtiger958/pytorch-computer-vision-basic
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/jtiger958/pytorch-computer-vision-tutorial
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/jtpils/treegan
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/juergenlandauer/Maya-Challenge
https://github.com/julik43/IIMAS-USCS
https://github.com/junebeomstics/tff
https://github.com/justinbellucci/cnn-visualizations-pytorch
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/justinjohn0306/EverybodyDanceNow-Colab
https://github.com/justinshenk/fer
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/justusschock/shape-constrained-network
https://github.com/jvoynow/ConvNet-Architectures
https://github.com/k-miran/hear
https://github.com/kabrau/FaceDetection
https://github.com/kagami/go-face
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/kaichengyan/facenet-darknet-pytorch
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/kainoj/keep-pulse
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/kaist-dmlab/SELFIE
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/kaiyangzhou/on-device-dg
https://github.com/kakaoenterprise/BroadFace
BroadFace: Looking at Tens of Thousands of People at Once for Face Recognition
https://github.com/kalaivani-s/self-attentive-sent-emb
https://github.com/kalelpark/ral
https://github.com/kamanphoebe/motiondetection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.