11 citations · 22 across the 6 of their papers we have counts for
6 papers
Strivec: Sparse Tri-Vector Radiance Fields
Quankai Gao, Qiangeng Xu, Hao Su +2
We propose Strivec, a novel neural representation that models a 3D scene as a radiance field with sparsely distributed and compactly factorized local tensor feature grids. Our appr…
Point-NeRF: Point-based Neural Radiance Fields
Qiangeng Xu, Zexiang Xu, Julien Philip +4
Volumetric neural rendering methods like NeRF generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. On the other hand…
Behind the Curtain: Learning Occluded Shapes for 3D Object Detection
Qiangeng Xu, Yiqi Zhong, Ulrich Neumann
Advances in LiDAR sensors provide rich 3D data that supports 3D scene understanding. However, due to occlusion and signal miss, LiDAR point clouds are in practice 2.5D as they cove…
Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry
Cho-Ying Wu, Qiangeng Xu, Ulrich Neumann
This work studies learning from a synergy process of 3D Morphable Models (3DMM) and 3D facial landmarks to predict complete 3D facial geometry, including 3D alignment, face orienta…
SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation
Qiangeng Xu, Yin Zhou, Weiyue Wang +2
In autonomous driving, a LiDAR-based object detector should perform reliably at different geographic locations and under various weather conditions. While recent 3D detection resea…
Accurate 3D Facial Geometry Prediction by Multi-Task, Multi-Modal, and Multi-Representation Landmark Refinement Network
Cho-Ying Wu, Qiangeng Xu, Ulrich Neumann
This work focuses on complete 3D facial geometry prediction, including 3D facial alignment via 3D face modeling and face orientation estimation using the proposed multi-task, multi…