Imperceptible 3D Point Cloud Attacks on Lattice-based Barycentric Coordinates
Authors: Keke Tang, Ziyong Du, Weilong Peng, Xiaofei Wang, Daizong Liu, Ligang Liu, Zhihong Tian
AAAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments validate that integrating these local parametric constraints into conventional adversarial attacks yields superior imperceptibility, outperforming state-of-the-art methods. |
| Researcher Affiliation | Academia | 1Guangzhou University 2University of Science and Technology of China 3Peking University |
| Pseudocode | No | The paper describes methods and formulations but does not contain a clearly labeled pseudocode or algorithm block. |
| Open Source Code | No | The paper does not contain any explicit statements about releasing source code for the described methodology, nor does it provide a link to a code repository. |
| Open Datasets | Yes | We evaluate on Model Net40 (Wu et al. 2015) and Shape Net Part (Chang et al. 2015), sampling 1,024 points per cloud following (Xiang, Qi, and Li 2019). |
| Dataset Splits | No | The paper mentions "sampling 1,024 points per cloud" and using Model Net40 and Shape Net Part datasets, but does not explicitly provide details about training/test/validation splits (e.g., percentages, sample counts, or specific split files). |
| Hardware Specification | Yes | Experiments are conducted on a workstation with dual 2.40 GHz CPUs, 128 GB RAM, and eight NVIDIA RTX 3090 GPUs. |
| Software Dependencies | No | We implement the LBC-constrained adversarial attack framework using Py Torch (Paszke et al. 2019). While PyTorch is mentioned, a specific version number for the library itself is not provided. |
| Experiment Setup | Yes | Following (Gu et al. 2019), we construct a permutohedral lattice with a resolution of r = 10 along each axis. For lattice subdivision, we compute each cell s density score and mean curvature, normalize them to [0,1], and calculate the subdivision criterion S( ) as their weighted sum with λd = 0.5. The subdivision threshold τ is set so that the top one-third of cells are subdivided. During lattice refinement, we optimize vertex positions over 2,000 iterations, setting λa = 10.0 to maintain cell angles. |