https://github.com/mg515/lie-detektor
Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognition
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/mgonzalezrivero/reef_learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mhagiwara/nanigonet
https://github.com/mic-dkfz/medicaldetectiontoolkit
https://github.com/miccunifi/scantalk
https://github.com/microsoft/computervision-recipes/blob/master/scenarios/similarity/02_state_of_the_art.ipynb
Classification is a Strong Baseline for Deep Metric Learning
https://github.com/microsoft/fb.resnet.torch
https://github.com/midas-research/text2facegan
Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions
https://github.com/midhun-em/face_recognition_facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mike07026/insightface_20190620
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/mikekestemont/deepscript
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mikelasz/fair-psp
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/mikgur/MADE_CV_1000_facial_landmarks
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks
https://github.com/mindlab-ai/mindcv/blob/main/examples/train_cifar_dynamic.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/resnet.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/vgg.py
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindslab-ai/faceshifter
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/mindslab-ai/hififace
HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping
https://github.com/mindslab-mwc5697/facenet_upload
https://github.com/mindspore-ai/contrib/tree/master/papers/Zero-DCE
Low-Light Image and Video Enhancement Using Deep Learning: A Survey
https://github.com/mindspore-ai/contrib/tree/master/papers/Zero-DCE%2B%2B
Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
https://github.com/mindspore-ai/models/blob/master/official/cv/retinanet/
https://github.com/mindspore-ai/models/blob/master/research/cv/LightCNN/
https://github.com/mindspore-ai/models/blob/master/research/cv/PGAN/
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/mindspore-ai/models/blob/master/research/cv/retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/mindspore-ai/models/blob/master/research/cv/retinanet_resnet152
https://github.com/mindspore-ai/models/tree/master/official/cv/centerface
CenterFace: Joint Face Detection and Alignment Using Face as Point
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet50_quant
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet_thor
https://github.com/mindspore-ai/models/tree/master/official/cv/retinaface_resnet50
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/mindspore-ai/models/tree/master/official/cv/sphereface
https://github.com/mindspore-ai/models/tree/master/official/cv/vgg16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-ai/models/tree/master/research/cv/DeepID
https://github.com/mindspore-ai/models/tree/master/research/cv/ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/mindspore-ai/models/tree/master/research/cv/FaceAttribute
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.