cuge1995/ICCV-2021-adversarial-attacks-and-defense
ICCV 2021 papers and code focus on adversarial attacks and defense
This resource curates research papers and associated code from ICCV 2021 focusing on adversarial attacks and defenses in computer vision. It provides insights into how machine learning models can be tricked and how to make them more robust. Researchers and security professionals working with image recognition, object detection, or other vision-based AI systems would use this to understand vulnerabilities and develop countermeasures.
No commits in the last 6 months.
Use this if you are a researcher or security professional investigating the resilience of AI models against malicious inputs or developing strategies to protect vision systems from adversarial manipulation.
Not ideal if you are looking for a plug-and-play tool for general computer vision tasks or a high-level overview of AI without technical depth.
Stars
11
Forks
—
Language
—
License
—
Category
Last pushed
Nov 05, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/cuge1995/ICCV-2021-adversarial-attacks-and-defense"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
MediaTek-NeuroPilot/mai21-learned-smartphone-isp
The official codebase for the Learned Smartphone ISP Challenge in MAI @ CVPR 2021
ashishpatel26/365-Days-Computer-Vision-Learning-Linkedin-Post
365 Days Computer Vision Learning Linkedin Post
extreme-assistant/ICCV2023-Paper-Code-Interpretation
ICCV2021/2019/2017 论文/代码/解读/直播合集，极市团队整理
amusi/daily-paper-computer-vision
记录每天整理的计算机视觉/深度学习/机器学习相关方向的论文
extreme-assistant/survey-computer-vision-2020
2020-2021年计算机视觉综述论文分方向整理