Search Results for author: Yanxin Ma

Found 4 papers, 1 papers with code

Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds

1 code implementation CVPR 2022 Yifan Zhang, Qingyong Hu, Guoquan Xu, Yanxin Ma, Jianwei Wan, Yulan Guo

To reduce the memory and computational cost, existing point-based pipelines usually adopt task-agnostic random sampling or farthest point sampling to progressively downsample input point clouds, despite the fact that not all points are equally important to the task of object detection.

Object object-detection +1

Dual-Neighborhood Deep Fusion Network for Point Cloud Analysis

no code implementations20 Aug 2021 Guoquan Xu, Hezhi Cao, Yifan Zhang, Jianwei Wan, Ke Xu, Yanxin Ma

To handle this prob-lem, a feature representation learning method, named Dual-Neighborhood Deep Fusion Network (DNDFN), is proposed to serve as an improved point cloud encoder for the task of non-idealized point cloud classification.

3D Point Cloud Classification Classification +2

Adaptive Channel Encoding for Point Cloud Analysis

no code implementations5 Dec 2021 Guoquan Xu, Hezhi Cao, Yifan Zhang, Jianwei Wan, Ke Xu, Yanxin Ma

Attention mechanism plays a more and more important role in point cloud analysis and channel attention is one of the hotspots.

Adaptive Channel Encoding Transformer for Point Cloud Analysis

no code implementations5 Dec 2021 Guoquan Xu, Hezhi Cao, Yifan Zhang, Yanxin Ma, Jianwei Wan, Ke Xu

Transformer plays an increasingly important role in various computer vision areas and remarkable achievements have also been made in point cloud analysis.

Point Cloud Classification

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