cuge1995/awesome-3D-point-cloud-attacks
List of state of the art papers, code, and other resources
This resource compiles leading research papers and code focused on understanding and mitigating security vulnerabilities in 3D point cloud systems. It provides insights into how malicious actors might subtly alter 3D data (like LiDAR scans or 3D models) to trick automated systems, as well as methods to defend against such attacks. Developers and researchers working with autonomous vehicles, robotics, or 3D computer vision will find this useful for building more robust systems.
111 stars. No commits in the last 6 months.
Use this if you are a developer or researcher focused on enhancing the security and robustness of deep learning models that process 3D point cloud data for tasks like object recognition or scene understanding.
Not ideal if you are looking for a ready-to-use software library for general 3D data processing or visualization, as this resource primarily curates academic research and related code for adversarial attacks and defenses.
Stars
111
Forks
14
Language
—
License
—
Category
Last pushed
Dec 03, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/cuge1995/awesome-3D-point-cloud-attacks"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Trusted-AI/adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion,...
bethgelab/foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
cleverhans-lab/cleverhans
An adversarial example library for constructing attacks, building defenses, and benchmarking both
DSE-MSU/DeepRobust
A pytorch adversarial library for attack and defense methods on images and graphs
BorealisAI/advertorch
A Toolbox for Adversarial Robustness Research