128 citations · 391 across the 19 of their papers we have counts for
6 papers · 1 filter
Learning to Infer Implicit Surfaces without 3D Supervision
Shichen Liu, Shunsuke Saito, Weikai Chen +1
Recent advances in 3D deep learning have shown that it is possible to train highly effective deep models for 3D shape generation, directly from 2D images. This is particularly inte…
Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networks
Junyi Pan, Xiaoguang Han, Weikai Chen +2
Reconstructing the 3D mesh of a general object from a single image is now possible thanks to the latest advances of deep learning technologies. However, due to the nontrivial diffi…
Learning Perspective Undistortion of Portraits
Yajie Zhao, Zeng Huang, Tianye Li +6
Near-range portrait photographs often contain perspective distortion artifacts that bias human perception and challenge both facial recognition and reconstruction techniques. We pr…
Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning
Shichen Liu, Tianye Li, Weikai Chen +1
Rendering bridges the gap between 2D vision and 3D scenes by simulating the physical process of image formation. By inverting such renderer, one can think of a learning approach to…
Soft Rasterizer: Differentiable Rendering for Unsupervised Single-View Mesh Reconstruction
Shichen Liu, Weikai Chen, Tianye Li +1
Rendering is the process of generating 2D images from 3D assets, simulated in a virtual environment, typically with a graphics pipeline. By inverting such renderer, one can think o…
SiCloPe: Silhouette-Based Clothed People
Ryota Natsume, Shunsuke Saito, Zeng Huang +4
We introduce a new silhouette-based representation for modeling clothed human bodies using deep generative models. Our method can reconstruct a complete and textured 3D model of a…