3 citations · 3 across the 5 of their papers we have counts for
5 papers
LAHNet: Local Attentive Hashing Network for Point Cloud Registration
Wentao Qu, Xiaoshui Huang, Liang Xiao
Most existing learning-based point cloud descriptors for point cloud registration focus on perceiving local information of point clouds to generate distinctive features. However, a…
Robust Single-Stage Fully Sparse 3D Object Detection via Detachable Latent Diffusion
Wentao Qu, Guofeng Mei, Jing Wang +3
Denoising Diffusion Probabilistic Models (DDPMs) have shown success in robust 3D object detection tasks. Existing methods often rely on the score matching from 3D boxes or pre-trai…
PCRDiffusion: Diffusion Probabilistic Models for Point Cloud Registration
Yue Wu, Yongzhe Yuan, Xiaolong Fan +3
We propose a new framework that formulates point cloud registration as a denoising diffusion process from noisy transformation to object transformation. During training stage, obje…
Multimodal Learning for Non-small Cell Lung Cancer Prognosis
Yujiao Wu, Yaxiong Wang, Xiaoshui Huang +3
This paper focuses on the task of survival time analysis for lung cancer. Although much progress has been made in this problem in recent years, the performance of existing methods…
DeepMMSA: A Novel Multimodal Deep Learning Method for Non-small Cell Lung Cancer Survival Analysis
Yujiao Wu, Jie Ma, Xiaoshui Huang +2
Lung cancer is the leading cause of cancer death worldwide. The critical reason for the deaths is delayed diagnosis and poor prognosis. With the accelerated development of deep lea…