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/karaposu/facexformer-pipeline
https://github.com/karlchahine/neural-cover-selection-for-image-steganography
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/kartik-3004/facexbench
https://github.com/kaseris/ILSVRCPlus
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/kaushal-k/Deep-Emotion
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network
https://github.com/kaushalshetty/Structured-Self-Attention
https://github.com/kawshik8/DL-project
https://github.com/kbpi314/iclust_paper
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/kbsriharsha/FacialEmotionAnalysis
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/kclip/localized-adaptive-risk-control
https://github.com/kdhingra307/temp
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/keetsky/Net_ghostVLAD-pytorch
https://github.com/keillernogueira/exploit-cnn-rs
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ken-power/CVND-FacialKeypointDetection
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/kenkenling/NLP
https://github.com/kenomo/industrial-clip
https://github.com/kentaroy47/BlazeFace_Person.pytorch
BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
https://github.com/keras-team/keras-applications
https://github.com/khai9xht/Multitask_head_pose
Simultaneous face detection and 360 degree headpose estimation
https://github.com/khaled2ahmed/k2a
https://github.com/khawajatalhahaseeb/Class-Activation-Map-Keras
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/khrlimam/facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/khurram702/StyleBasedGAN
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/khyeyoon/face_recognition
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/kim1102/PPL-MFR
https://github.com/kingcong/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/kingcong/Zero-DCE
Low-Light Image and Video Enhancement Using Deep Learning: A Survey
https://github.com/kingcong/Zero-DCE-
Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
https://github.com/kingcong/gpu_ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/kingcong/gpu_FaceAttribute
https://github.com/kingcong/gpu_HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/kingcong/gpu_SE-Net
https://github.com/kingcong/resnet
https://github.com/kingsj0405/pulse-any-image
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/kiranu1024/deep-learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.