activity
20222024
most citedPoint Cloud Upsampling via Cascaded Refinement Network

7 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

1st Place Solution for ICCV 2023 OmniObject3D Challenge: Sparse-View Reconstruction

Hang Du, Yaping Xue, Weidong Dai +2

In this report, we present the 1st place solution for ICCV 2023 OmniObject3D Challenge: Sparse-View Reconstruction. The challenge aims to evaluate approaches for novel view synthes…

cs.CV2024

Arbitrary-Scale Point Cloud Upsampling by Voxel-Based Network with Latent Geometric-Consistent Learning

Hang Du, Xuejun Yan, Jingjing Wang +2

Recently, arbitrary-scale point cloud upsampling mechanism became increasingly popular due to its efficiency and convenience for practical applications. To achieve this, most previ…

cs.CV2023★ 2 cited

Rethinking the Approximation Error in 3D Surface Fitting for Point Cloud Normal Estimation

Hang Du, Xuejun Yan, Jingjing Wang +2

Most existing approaches for point cloud normal estimation aim to locally fit a geometric surface and calculate the normal from the fitted surface. Recently, learning-based methods…

cs.CV2022★ 1 cited

FBNet: Feedback Network for Point Cloud Completion

Xuejun Yan, Hongyu Yan, Jingjing Wang +5

The rapid development of point cloud learning has driven point cloud completion into a new era. However, the information flows of most existing completion methods are solely feedfo…

cs.CV2022★ 7 cited

Point Cloud Upsampling via Cascaded Refinement Network

Hang Du, Xuejun Yan, Jingjing Wang +2

Point cloud upsampling focuses on generating a dense, uniform and proximity-to-surface point set. Most previous approaches accomplish these objectives by carefully designing a sing…