10 citations · 10 across the 2 of their papers we have counts for
5 papers
Stereopagnosia: Fooling Stereo Networks with Adversarial Perturbations
Alex Wong, Mukund Mundhra, Stefano Soatto
We study the effect of adversarial perturbations of images on the estimates of disparity by deep learning models trained for stereo. We show that imperceptible additive perturbatio…
Targeted Adversarial Perturbations for Monocular Depth Prediction
Alex Wong, Safa Cicek, Stefano Soatto
We study the effect of adversarial perturbations on the task of monocular depth prediction. Specifically, we explore the ability of small, imperceptible additive perturbations to s…
Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction
Alex Wong, Byung-Woo Hong, Stefano Soatto
Supervised learning methods to infer (hypothesize) depth of a scene from a single image require costly per-pixel ground-truth. We follow a geometric approach that exploits abundant…
Dense Depth Posterior (DDP) from Single Image and Sparse Range
Yanchao Yang, Alex Wong, Stefano Soatto
We present a deep learning system to infer the posterior distribution of a dense depth map associated with an image, by exploiting sparse range measurements, for instance from a li…
Geo-Supervised Visual Depth Prediction
Xiaohan Fei, Alex Wong, Stefano Soatto
We propose using global orientation from inertial measurements, and the bias it induces on the shape of objects populating the scene, to inform visual 3D reconstruction. We test th…