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Liu et al. propose adversarial attacks on physical parameters of images, which can be manipulated efficiently through differentiable renderer. In particular, they propose adversarial lighting and adversarial geometry; in both cases, an image is assumed to be a function of lighting and geometry, generated by a differentiable renderer. By directly manipulating these latent variables, more realistic looking adversarial examples can be generated for synthetic images as shown in Figure 1. https://i.imgur.com/uh2pj9w.png Figure 1: Comparison of the proposed attack with known attacks applied to large perturbations, $L_\infty \approx 0.82$. Also find this summary at [davidstutz.de](https://davidstutz.de/category/reading/).
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