The paper Variotional Bayesian Inference for Audio-Visual Tracking of Multiple Speakers has been published in the IEEE Transactions on Pattern Analysis and Machine Intelligence (journal with one of the highest impact score in the category computational intelligence). This work is part of the Ph.D. thesis of Yutong Ban, now with the Computer Science and Artificial …
In signal processing and in computer vision, some of the most powerful tracking methods are based on the Kalman filter. The latter belongs to the unsupervised class of machine learning techniques and may well be viewed either as the simplest dynamic Bayesian network (DBN) or as a state-space model: it recursively predicts over time a …
Seminar by Stéphane Lathuilière, Télécom Paris Friday, 18 October 2019, 14:30 – 15:30, room F107 INRIA Montbonnot Saint-Martin Abstract: Generating realistic images and videos has countless applications in different areas, ranging from photography technologies to e-commerce business. Recently, deep generative approaches have emerged as effective techniques for generation tasks. In this talk, we will first present …
Xavier Alameda-Pineda has become an IEEE Senior Member on February 1st, 2019. The grade of Senior Member requires experience reflecting professional maturity as an engineer, scientist, educator, technical executive, or originator in IEEE-designated fields for a total of 10 years and have demonstrated 5 years of significant performance.
The Kinovis Multiple-Speaker Tracking Dataset Data | pdf from arXiv | download | reference The Kinovis multiple speaker tracking (Kinovis-MST) datasets contain live acoustic recordings of multiple moving speakers in a reverberant environment. The data were recorded in the Kinovis multiple-camera laboratory at INRIA Grenoble Rhône-Alpes. The room size is 10.2 m × 9.9 m × 5.6 …
Sparse representation, dictionary learning, and deep neural networks: their connections and new algorithms
Seminar by Mostafa Sadeghi, Sharif University of Technology, Tehran Tuesday 19 June 2018, 14:30 – 15:30, room F107 INRIA Montbonnot Saint-Martin Abstract. Over the last decade, sparse representation, dictionary learning, and deep artificial neural networks have dramatically impacted on the signal processing and machine learning areas by yielding state-of-the-art results in a variety of tasks, …
PhD defense by Israel D. Gebru Friday 13 April 2018, 9:30 – 10:30, Grand Amphithéatre INRIA Grenoble Rhône-Alpes, Montbonnot Saint-Martin In recent years, there has been a growing interest in human-robot interaction (HRI), with the aim to enable robots to naturally interact and communicate with humans. Natural interaction implies that robots not only need to …
The following journal paper has just been published: Richard Marriott, Alexander Pashevich, and Radu Horaud. Plane Extraction from Depth Data Using a Gaussian Mixture Regression Model. Pattern Recognition Letters. vol. 110, pages 44-50, 2018. The paper is free for download from our publication page or directly from Elsevier.