28 citations · 42 across the 3 of their papers we have counts for
4 papers
Unleashing the Multi-View Fusion Potential: Noise Correction in VLM for Open-Vocabulary 3D Scene Understanding
Xingyilang Yin, Jiale Wang, Xi Yang +3
Recent open-vocabulary 3D scene understanding approaches mainly focus on training 3D networks through contrastive learning with point-text pairs or by distilling 2D features into 3…
MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency
Mingye Xu, Mutian Xu, Tong He +4
Masked Modeling (MM) has demonstrated widespread success in various vision challenges, by reconstructing masked visual patches. Yet, applying MM for large-scale 3D scenes remains a…
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
Mutian Xu, Runyu Ding, Hengshuang Zhao +1
We introduce Position Adaptive Convolution (PAConv), a generic convolution operation for 3D point cloud processing. The key of PAConv is to construct the convolution kernel by dyna…
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud
Mutian Xu, Junhao Zhang, Zhipeng Zhou +3
In 2D image processing, some attempts decompose images into high and low frequency components for describing edge and smooth parts respectively. Similarly, the contour and flat are…