1 citations · 2 across the 10 of their papers we have counts for
6 papers · 1 filter
Late-decoupled 3D Hierarchical Semantic Segmentation with Semantic Prototype Discrimination based Bi-branch Supervision
Shuyu Cao, Chongshou Li, Jie Xu +2
3D hierarchical semantic segmentation (3DHS) is crucial for embodied intelligence applications that demand a multi-grained and multi-hierarchy understanding of 3D scenes. Despite t…
ModelNet40-E: An Uncertainty-Aware Benchmark for Point Cloud Classification
Pedro Alonso, Tianrui Li, Chongshou Li
We introduce ModelNet40-E, a new benchmark designed to assess the robustness and calibration of point cloud classification models under synthetic LiDAR-like noise. Unlike existing…
GeoCD: A Differential Local Approximation for Geodesic Chamfer Distance
Pedro Alonso, Tianrui Li, Chongshou Li
Chamfer Distance (CD) is a widely adopted metric in 3D point cloud learning due to its simplicity and efficiency. However, it suffers from a fundamental limitation: it relies solel…
LLM-Guided Taxonomy and Hierarchical Uncertainty for 3D Point Cloud Active Learning
Chenxi Li, Nuo Chen, Fengyun Tan +4
We present a novel active learning framework for 3D point cloud semantic segmentation that, for the first time, integrates large language models (LLMs) to construct hierarchical la…
Rethinking Gradient-based Adversarial Attacks on Point Cloud Classification
Jun Chen, Xinke Li, Mingyue Xu +2
Gradient-based adversarial attacks are widely used to evaluate the robustness of 3D point cloud classifiers, yet they often rely on uniform update rules that neglect point-wise het…
Controllable 3D Outdoor Scene Generation via Scene Graphs
Yuheng Liu, Xinke Li, Yuning Zhang +6
Three-dimensional scene generation is crucial in computer vision, with applications spanning autonomous driving, gaming and the metaverse. Current methods either lack user control…