116 citations · 1.1k across the 96 of their papers we have counts for
7 papers · 1 filter
Dynamics and Reachability of Learning Tasks
Alessandro Achille, Glen Mbeng, Stefano Soatto
We compute the transition probability between two learning tasks, and show that it decomposes into two factors. The first depends on the geometry of the loss landscape of a model t…
Conditional Prior Networks for Optical Flow
Yanchao Yang, Stefano Soatto
Classical computation of optical flow involves generic priors (regularizers) that capture rudimentary statistics of images, but not long-range correlations or semantics. On the oth…
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…
Visual-Inertial Object Detection and Mapping
Xiaohan Fei, Stefano Soatto
We present a method to populate an unknown environment with models of previously seen objects, placed in a Euclidean reference frame that is inferred causally and on-line using mon…
Input and Weight Space Smoothing for Semi-supervised Learning
Safa Cicek, Stefano Soatto
We propose regularizing the empirical loss for semi-supervised learning by acting on both the input (data) space, and the weight (parameter) space. We show that the two are not equ…
SaaS: Speed as a Supervisor for Semi-supervised Learning
Safa Cicek, Alhussein Fawzi, Stefano Soatto
We introduce the SaaS Algorithm for semi-supervised learning, which uses learning speed during stochastic gradient descent in a deep neural network to measure the quality of an ite…
OATM: Occlusion Aware Template Matching by Consensus Set Maximization
Simon Korman, Mark Milam, Stefano Soatto
We present a novel approach to template matching that is efficient, can handle partial occlusions, and comes with provable performance guarantees. A key component of the method is…