Runsong Zhu

Wuhan University | WHU · State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing

Panoptic lifting is an effective technique to address the 3D panoptic segmentation task by unprojecting 2D panoptic segmentations from multi-views to 3D scene. However, the quality of its results largely depends on the 2D segmentations, which could be noisy and error-prone, so its performance often drops significantly for complex scenes. In this wo...

Reconstructing 3D geometry from \emph{unoriented} point clouds can benefit many downstream tasks. Recent methods mostly adopt a neural shape representation with a neural network to represent a signed distance field and fit the point cloud with an unsigned supervision. However, we observe that using unsigned supervision may cause severe ambiguities...

This paper presents a neural network for robust normal estimation on point clouds, named AdaFit, that can deal with point clouds with noise and density variations. Existing works use a network to learn point-wise weights for weighted least squares surface fitting to estimate the normals, which has difficulty in finding accurate normals in complex r...

In large-scale road environment, point-based methods require dynamic calculations, and voxel-based methods often lose a lot of information when balancing resolution and performance. To overcome the drawbacks of the above two classical methods, this paper proposes a general network architecture that combines bi-level convolution and dynamic graph ed...