https://github.com/huawenwei4/dfl
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
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/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
https://github.com/hukkelas/DSFD-Pytorch-Inference
https://github.com/hukkelas/progan-pytorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/human-analysis/RankGAN
https://github.com/human-analysis/secure-face-matching
https://github.com/humbleOldSage/Triplet-Loss-for-Personal-dataset
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/huybik/GAN-Experiments-Pytorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/huybik/GANs-Pytorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/huyhieupham/3D-Face-Recognition
Learning from Millions of 3D Scans for Large-scale 3D Face Recognition
https://github.com/huytranvan2010/RetinaNet-Understanding
https://github.com/hweersot/darknet-custom
https://github.com/hyang0129/foodclassapp
https://github.com/hyhchaos/FakePolisher
FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction
https://github.com/hz-ants/pointnet.pytorch
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/hzh8311/pyhowfar
https://github.com/hzlsaber/sida
https://github.com/i6092467/diff-bias-proxies
https://github.com/iChenning/facedetection
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/iPRoBe-lab/semi-adversarial-networks
Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images
https://github.com/iacopomasi/face_specific_augm
https://github.com/iamgroot42/A-LINK
https://github.com/ibadr/RetinaFace
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/ibbu10/Facial-Landmark-Detection-Using-CNN
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/ibendrup/MulticolumnNetwork
https://github.com/icey-zhang/MTCNN_paddle
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/icey-zhang/RetinaFace_paddle
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/idealo/image-super-resolution
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/iiTzFrankie/DCJT
https://github.com/iigroup/mm-celeba-hq-dataset
TediGAN: Text-Guided Diverse Face Image Generation and Manipulation
https://github.com/iitmcvg/Demo-of-face-detection-and-counting-
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/ililily/retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/imanlab/deep_movement_primitives
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/immuno121/audio_source_classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.