Publication
Scale-invariant representation of light field images for object recognition and tracking
Related publications (49)
Aggregating Spatial and Photometric Context for Photometric Stereo
Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...
EPFL2024Perspective Aware Road Obstacle Detection
Pascal Fua, Mathieu Salzmann, Krzysztof Maciej Lis, Sina Honari
While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this letter, we account for this by c ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023Time Dependent Image Generation of Plants from Incomplete Sequences with CNN-Transformer
Data imputation of incomplete image sequences is an essential prerequisite for analyzing and monitoring all development stages of plants in precision agriculture. For this purpose, we propose a conditional Wasserstein generative adversarial network TransGr ...
SPRINGER INTERNATIONAL PUBLISHING AG2022A Downscaling Intercomparison Study: The Representation of Slope- and Ridge-Scale Processes in Models of Different Complexity
Varun Sharma, Franziska Gerber, Dylan Stewart Reynolds
Spatially distributed meteorological information at the slope scale is relevant for many processes in complex terrain, yet information at this sub-km spatial resolution is difficult to obtain. While downscaling to kilometer resolutions is well described in ...
FRONTIERS MEDIA SA2022FANOK: Knockoffs in Linear Time
We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large-scale feature selection problems. Identifying the knockoff distribution requires solving a large-scale semidefinite progra ...
SIAM PUBLICATIONS2021Fast and Space Efficient Spectral Sparsification in Dynamic Streams
Mikhail Kapralov, Jakab Tardos, Navid Nouri, Aidasadat Mousavifar
In this paper, we resolve the complexity problem of spectral graph sparcification in dynamic streams up to polylogarithmic factors. Using a linear sketch we design a streaming algorithm that uses (O) over tilde (n) space, and with high probability, recover ...
ASSOC COMPUTING MACHINERY2020Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains
Serge Vaudenay, Fatma Betül Durak
Feistel Networks (FN) are now being used massively to encrypt credit card numbers through format-preserving encryption. In our work, we focus on FN with two branches, entirely unknown round functions, modular additions (or other group operations), and when ...
2018Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains
Serge Vaudenay, Fatma Betül Durak
Feistel Networks (FN) are now being used massively to encrypt credit card numbers through format-preserving encryption. In our work, we focus on FN with two branches, entirely unknown round functions, modular additions (or other group operations), and when ...
ePrint2018Maya Codical Glyph Segmentation: A Crowdsourcing Approach
Daniel Gatica-Perez, Jean-Marc Odobez, Gülcan Can
This paper focuses on the crowd-annotation of an ancient Maya glyph dataset derived from the three ancient codices that survived up to date. More precisely, non-expert annotators are asked to segment glyph-blocks into their constituent glyph entities. As a ...
2018General Proximal Gradient Method: A Case for Non-Euclidean Norms
Volkan Cevher, Ya-Ping Hsieh, Marwa El Halabi, Cong Bang Vu, Van Quang Nguyen
In this paper, we consider composite convex minimization problems. We advocate the merit of considering Generalized Proximal gradient Methods (GPM) where the norm employed is not Euclidean. To that end, we show the tractability of the general proximity ope ...
2017