S
Stefano Soatto
Researcher at University of California, Los Angeles
Publications - 499
Citations - 27815
Stefano Soatto is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Motion estimation & Image segmentation. The author has an hindex of 78, co-authored 499 publications receiving 23597 citations. Previous affiliations of Stefano Soatto include University of California & University of California, Davis.
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Zero Shot Learning with the Isoperimetric Loss
TL;DR: In this article, the authors introduce the isoperimetric loss as a regularization criterion for learning the map from a visual representation to a semantic embedding, to be used to transfer knowledge to unknown classes in a zero-shot learning setting.
Proceedings ArticleDOI
Feature tracking and object recognition on a hand-held
Taehee Lee,Stefano Soatto +1 more
TL;DR: A visual recognition system operating on a hand-held device, with the help of an efficient and robust feature tracking and an object recognition mechanism that can be used for interactive mobile applications is demonstrated.
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Input and Weight Space Smoothing for Semi-supervised Learning
Safa Cicek,Stefano Soatto +1 more
TL;DR: In this paper, the authors proposed a method to regularize the empirical loss for semi-supervised learning by acting on both the input (data) space and the weight (parameter) space.
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Harnessing Unrecognizable Faces for Face Recognition.
TL;DR: In this paper, the authors propose a measure of recognizability of a face image that leverages a key empirical observation: an embedding of face images, implemented by a deep neural network trained using mostly recognizable identities, induces a partition of the hypersphere whereby unrecognizable identities cluster together.
Book ChapterDOI
Mumford-Shah for Segmentation and Stereo
TL;DR: It is shown how the use of simultaneous piecewise smooth image segmentation on a set of calibrated 2D images of a common 3D scene may be utilized for reconstructing the unknown shapes and radiances of scene objects.