LighTN: Light-weight Transformer Network for Performance-overhead Tradeoff in Point Cloud Downsampling

13 February 2022

Papers citing "LighTN: Light-weight Transformer Network for Performance-overhead Tradeoff in Point Cloud Downsampling"

8 / 8 papers shown

Title
SAMBLE: Shape-Specific Point Cloud Sampling for an Optimal Trade-Off Between Local Detail and Global Uniformity Chengzhi Wu Yuxin Wan Hao Fu Julius Pfrommer Zeyun Zhong Junwei Zheng Jiaming Zhang Jürgen Beyerer 3DPC 54 0 0 28 Apr 2025
REPS: Reconstruction-based Point Cloud Sampling Guoqing Zhang Wenbo Zhao Jian Liu Xianming Liu 3DPC 28 0 0 08 Mar 2024
LiDAR-Generated Images Derived Keypoints Assisted Point Cloud Registration Scheme in Odometry Estimation Haizhou Zhang Xianjia Yu Sier Ha Tomi Westerlund 3DPC 31 6 0 19 Sep 2023
Self-Attentive Pooling for Efficient Deep Learning Fang Chen Gourav Datta Souvik Kundu P. Beerel 79 6 0 16 Sep 2022
Mobile-Former: Bridging MobileNet and Transformer Yinpeng Chen Xiyang Dai Dongdong Chen Mengchen Liu Xiaoyi Dong Lu Yuan Zicheng Liu ViT 177 476 0 12 Aug 2021
Transformer in Transformer Kai Han An Xiao Enhua Wu Jianyuan Guo Chunjing Xu Yunhe Wang ViT 284 1,524 0 27 Feb 2021
Attention Models for Point Clouds in Deep Learning: A Survey Xu Wang Yi Jin Yigang Cen Tao Wang Yidong Li 3DPC 28 12 0 22 Feb 2021
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 222 14,103 0 02 Dec 2016