2026
Lipschitz Optimization for Formal Verification of Homographies
CVPR 2026
The adoption of vision neural networks in regulated industries requires formal robustness guarantees, especially in safety-critical domains such as healthcare, autonomous vehicles, and aerospace. However, current approaches are confined to incomplete statistical verification or robustness to p-norm