83 citations · 120 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects
Ruihai Wu, Yan Zhao, Kaichun Mo +7
Perceiving and manipulating 3D articulated objects (e.g., cabinets, doors) in human environments is an important yet challenging task for future home-assistant robots. The space of…
MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras
Xuelin Chen, Weiyu Li, Daniel Cohen-Or +2
Synthesizing novel views of dynamic humans from stationary monocular cameras is a specialized but desirable setup. This is particularly attractive as it does not require static sce…
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…