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.
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https://github.com/koshian2/swd-pytorch
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https://github.com/krantirk/Face-detection-and-counting-
FaceNet: A Unified Embedding for Face Recognition and Clustering
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PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
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Very Deep Convolutional Networks for Large-Scale Image Recognition
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ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/kuaikuaikim/DFace
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/kuangliu/pytorch-fpn
https://github.com/kukby/Mish-semantic-segmentation-pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/kukico/learning
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https://github.com/kwotsin/TensorFlow-ENet
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Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/kyranstar/Narcissus
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https://github.com/kzmttr/UMDFA
https://github.com/lab-midas/med_segmentation
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https://github.com/laohur/LearnToCompareText
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Exploiting temporal and depth information for multi-frame face anti-spoofing
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High-Resolution Representations for Labeling Pixels and Regions
https://github.com/larsoncs/face_detect
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/layumi/Person_reID_baseline_pytorch
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/leebebeto/pytorch-implementation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/leejieun51/transformer
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https://github.com/leenaali1114/Hierarchical-Image-Clustering---Unsupervised-Learning
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.