3 citations · 3 across the 1 of their papers we have counts for
4 papers
SinGRAV: Learning a Generative Radiance Volume from a Single Natural Scene
Yujie Wang, Xuelin Chen, Baoquan Chen
We present a 3D generative model for general natural scenes. Lacking necessary volumes of 3D data characterizing the target scene, we propose to learn from a single scene. Our key…
Towards a Neural Graphics Pipeline for Controllable Image Generation
Xuelin Chen, Daniel Cohen-Or, Baoquan Chen +1
In this paper, we leverage advances in neural networks towards forming a neural rendering for controllable image generation, and thereby bypassing the need for detailed modeling in…
Multimodal Shape Completion via Conditional Generative Adversarial Networks
Rundi Wu, Xuelin Chen, Yixin Zhuang +1
Several deep learning methods have been proposed for completing partial data from shape acquisition setups, i.e., filling the regions that were missing in the shape. These methods,…
Unpaired Point Cloud Completion on Real Scans using Adversarial Training
Xuelin Chen, Baoquan Chen, Niloy J. Mitra
As 3D scanning solutions become increasingly popular, several deep learning setups have been developed geared towards that task of scan completion, i.e., plausibly filling in regio…