Generative Face Parsing Map Guided 3D Face Reconstruction Under Occluded Scenes
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Abstract (arXiv)
Over the past few years, single-view 3D face reconstruction methods can produce beautiful 3D models. Nevertheless,the input of these works is unobstructed faces.We describe a system designed to reconstruct convincing face texture in the case of occlusion.Motivated by parsing facial features,we propose a complete face parsing map generation method guided by landmarks.We estimate the 2D face structure of the reasonable position of the occlusion area,which is used for the construction of 3D texture.An excellent anti-occlusion face reconstruction method should ensure the authenticity of the output,including the topological structure between the eyes,nose, and mouth. We extensively tested our method and its components, qualitatively demonstrating the rationality of our estimated facial structure. We conduct extensive experiments on general 3D face reconstruction tasks as concrete examples to demonstrate the method's superior regulation ability over existing methods often break down.We further provide numerous quantitative examples showing that our method advances both the quality and the robustness of 3D face reconstruction under occlusion scenes.
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References · 20
- 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
- 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,988
- 2014Conditional Generative Adversarial Netscited by 2,162
- 2017Rethinking Atrous Convolution for Semantic Image Segmentationcited by 2,161
- 2018Spectral Normalization for Generative Adversarial Networkscited by 1,636
- 2015Spatial Transformer Networkscited by 1,429
- 2016Instance Normalization: The Missing Ingredient for Fast Stylizationcited by 1,198
- 2021Segmenter: Transformer for Semantic Segmentationcited by 855
- 2017Unsupervised Image-to-Image Translation Networkscited by 603
- 2014Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFscited by 554
- 2016A Learned Representation For Artistic Stylecited by 341
- 2017AttGAN: Facial Attribute Editing by Only Changing What You Wantcited by 242
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- 2020Towards Fast, Accurate and Stable 3D Dense Face Alignmentcited by 219
- 2019EdgeConnect: Generative Image Inpainting with Adversarial Edge Learningcited by 163
- 2018Patch-Based Image Inpainting with Generative Adversarial Networkscited by 70
- 2020Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networkscited by 51
- 2014Generative Adversarial Networkscited by 33
- 2021CoMoGAN: continuous model-guided image-to-image translationcited by 27
- 2016Deep Identity-aware Transfer of Facial Attributescited by 13
- 2017Face Parsing via a Fully-Convolutional Continuous CRF Neural Networkcited by 7
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