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/artynet/darknet-alexeyAB
https://github.com/ashawkey/RAD-NeRF
Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition
https://github.com/ashishpatel26/BrainMRI-Segmentation-Keras
https://github.com/ashokpant/video_processing_opencv_cpp
https://github.com/ashushekar/VGG16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ashutosh1919/FaceGenerationStyleGAN
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/asmadotgh/unc-net
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/asprenger/keras_fc_densenet
https://github.com/astoff/dog-breed-app
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/astoycos/Mini_Project2
https://github.com/atom06/Tiny_Faces_in_Tensorflow_v2
https://github.com/audio-df-ucb/clonedvoicedetection
https://github.com/aurelien-peden/Deep-Learning-paper-implementations
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/autonomobil/SCDND-P2_Traffic-Sign-Classifier
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/autonomousvision/frequency_bias
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/av-savchenko/emotiefflib
Frame-level Prediction of Facial Expressions, Valence, Arousal and Action Units for Mobile Devices
https://github.com/aviros/pointnet_totations
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/aviros/roatationPointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/avishai111/One-Class-Learning-with-Adaptive-Centroid-Shift-for-Audio-Deepfake-Detection
One-Class Learning with Adaptive Centroid Shift for Audio Deepfake Detection
https://github.com/avocardio/resnet_vs_convnext
https://github.com/avuku06/G
A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing
https://github.com/axium/Blind-Image-Deconvolution-using-Deep-Generative-Priors
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/axmoyal/Steganalysis-with-CNN
https://github.com/ayushdabra/drone-images-semantic-segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushdabra/lunar-landscape-images-segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushdabra/retinal-oct-images-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushgupta9198/gan
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushgupta9198/stylegan
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushpalak/darknet_cokebottles
https://github.com/ayushpalak/darknet_multi_cokebottles
https://github.com/azshue/TPT
https://github.com/b5071/pulse-rev
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/b8goal/PIRL-Residual-network
https://github.com/bailvwangzi/repulsion_loss_ssd
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/bakerv/fer-webcam
Facial Emotion Recognition: State of the Art Performance on FER2013
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.