1.0Breaking Depth Estimation Models with Semantic Adversarial Attackshttps://mscvprojects.ri.cmu.edu/2025team12-2Methodology - Breaking Depth Estimation Models with Semantic Adversarial Attacksrich600338<blockquote class="wp-embedded-content" data-secret="x77pbJaMKh"><a href="https://mscvprojects.ri.cmu.edu/2025team12-2/experiments/">Methodology</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://mscvprojects.ri.cmu.edu/2025team12-2/experiments/embed/#?secret=x77pbJaMKh" width="600" height="338" title="“Methodology” — Breaking Depth Estimation Models with Semantic Adversarial Attacks" data-secret="x77pbJaMKh" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script>
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Our approach intends to experimentally evaluate the robustness of monocular depth estimation (MDE) models. Specifically, we seek to develop a diagnostic toolbox that can allow you to systematically sample failure modes for common MDEs. This objective can be effectively seen below. Camera Parameterization To identify failures in an MDE model, we parameterize the camera with … Continue reading ""https://mscvprojects.ri.cmu.edu/2025team12-2/wp-content/uploads/sites/125/2025/12/image.png