Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Yalniz, I. Zeki"'
The proliferation of AI-generated content and sophisticated video editing tools has made it both important and challenging to moderate digital platforms. Video watermarking addresses these challenges by embedding imperceptible signals into videos, al
Externí odkaz:
http://arxiv.org/abs/2412.09492
The statistical distribution of content uploaded and searched on media sharing sites changes over time due to seasonal, sociological and technical factors. We investigate the impact of this "content drift" for large-scale similarity search tools, bas
Externí odkaz:
http://arxiv.org/abs/2308.02752
Autor:
Coleman, Cody, Chou, Edward, Katz-Samuels, Julian, Culatana, Sean, Bailis, Peter, Berg, Alexander C., Nowak, Robert, Sumbaly, Roshan, Zaharia, Matei, Yalniz, I. Zeki
Many active learning and search approaches are intractable for large-scale industrial settings with billions of unlabeled examples. Existing approaches search globally for the optimal examples to label, scaling linearly or even quadratically with the
Externí odkaz:
http://arxiv.org/abs/2007.00077
Label noise is increasingly prevalent in datasets acquired from noisy channels. Existing approaches that detect and remove label noise generally rely on some form of supervision, which is not scalable and error-prone. In this paper, we propose NoiseR
Externí odkaz:
http://arxiv.org/abs/2003.06729
This paper presents a study of semi-supervised learning with large convolutional networks. We propose a pipeline, based on a teacher/student paradigm, that leverages a large collection of unlabelled images (up to 1 billion). Our main goal is to impro
Externí odkaz:
http://arxiv.org/abs/1905.00546
Autor:
Rameswar Panda, Amit K. Roy-Chowdhury
Person re-identification is the problem of associating observations of targets in different non-overlapping cameras. Most of the existing learning-based methods have resulted in improved performance on standard re-identification benchmarks, but at th
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference