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/trzy/VGG16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ttruty/facial-feature-mouse-control
Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression
https://github.com/tueboesen/Active-Learning
Cost-Effective Active Learning for Deep Image Classification
https://github.com/tueboesen/a-optimal-active-learning
Cost-Effective Active Learning for Deep Image Classification
https://github.com/tungdt92/GFA-CNN
Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing
https://github.com/tuvovan/Zero_DCE_TF
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/tuyentv2009/Face-Recognition-
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/twyunting/Deepfake_Video_Classifier
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/u7javed/Image-Enhancer-via-ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/u7javed/Image-Super-Resolution-Enhancer-via-ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/uclaml/Padam
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/udaya2899/deepfake-detection
Exposing DeepFake Videos By Detecting Face Warping Artifacts
https://github.com/ugail/FaciaIBeautyIEEESKIMA2023
https://github.com/uladzislau-varabei/progressively_growing_gan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/ultralytics/yolov5
https://github.com/umd-fire-coml/2020-Face-Generation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/umgupta/2d-slice-set-networks
https://github.com/umitkacar/ai-edge-computing
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
https://github.com/ung200/thats-what-obama-said
https://github.com/unsky/RetinaNet
https://github.com/unsky/focal-loss
https://github.com/usnistgov/image-classification-resnet50
https://github.com/usnistgov/image-regression-resnet50
https://github.com/ut-vision/rot-mvgaze
Learning-by-Novel-View-Synthesis for Full-Face Appearance-Based 3D Gaze Estimation
https://github.com/utsawk/CarND-Traffic-Sign-Classifier-Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/uw-hai/limeade
https://github.com/v-trungdt21/MaskTheFace
https://github.com/valentingol/GANJax
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/vantupham/darknet
https://github.com/varennes/deep-autoencoder
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/varshaneya/Res-SE-Net
https://github.com/varununleashed/tiny_faces_temp
https://github.com/vayuvegula/kerasModels
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vbonifaci/l1opt
https://github.com/vendyv/CodeSpeedy_Internship
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.