Tag: ganfit

• GANFIT Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction (01 May 2021)
  

  This is my reading note for GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction. The code is available in GANFit. GANFit reconstructs high quality texture and geometry from a single image with precise identity recovery. To do this, it utilizes GANs to train a very powerful generator of facial texture in UV space. Then, it revisits the original 3D Morphable Models (3DMMs) fitting approaches making use of non-linear optimization to find the optimal latent parameters that best reconstruct the test image but under a new perspective. It optimizes the parameters with the supervision of pretrained deep identity features through our end-to-end differentiable framework.

• Avatarme Realistically renderable 3d facial reconstruction in-The-wild (28 Apr 2021)
  

  This is reading note for Avatarme: Realistically renderable 3d facial reconstruction ‘in-The-wild’, which was published in CVPR 2020 and code is available in github. Avatarme aims to reconstruct photorealistic 3D faces from a single “in-the-wild” image with an increasing level of detail. It could generate 4K by 6K-resolution 3D faces from a single low-resolution image that, for the first time, bridges the uncanny valley.

• My Paper Reading List for 3D Face Reconstructions (20 Mar 2021)
  

  Here is my paper reading lsit for 3D face reconstructions based on Papers with Code. 3D face reconstruction is the task of reconstructing a face from an image into a 3D form (or mesh). Most of the papers on the list are between 2017~2020.