Author's posts

Deformations in Deep Models for Image and Video Generation

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 …

Continue reading

The Kinovis-MST Dataset

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 …

Continue reading

Book co-edited by Xavier Alameda-Pineda

New book published by Academic Press (Elsevier), entitled “Multimodal Behavior Analysis in the Wild”, edited by Xavier Alameda Pineda, Elisa Ricci and Nicu Sebe. The book gathers 20 chapters written by 75 researchers from all over the world.  

ACM SIGMM Rising Star Award 2018

The 2018 winner of the prestigious ACM Special Interest Group on Multimedia (SIGMM) Rising Star Award is our colleague Dr. Xavier Alameda-Pineda. The award is given in recognition of his contribution to multimodal social behavior understanding. Congratulations Xavi!

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, …

Continue reading

Audio-Visual Analysis in the Framework of Humans Interacting with Robots

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 …

Continue reading

Plane Extraction from Depth-Data

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.

Biosignal-based speech processing for communication rehabilitation

Seminar  by Thomas Hueber, CNRS, GIPSA-lab, Grenoble Thursday 8 February, 10:00 – 11:00, room F107 INRIA Montbonnot Saint-Martin Abstract. Propelled by the progress of machine learning, speech technologies such as automatic speech recognition and text-to-speech synthesis have become enough advanced to be deployed in several consumer products and used in our daily lives. However, using …

Continue reading

A Bayesian Framework for Head Pose Estimation and Tracking

PhD defense by Vincent Drouard Monday 18 December 2017, 11:00 – 12:00, Grand Amphithéatre INRIA Montbonnot Saint-Martin In this thesis, we address the well-known problem of head-pose estimation in the context of human-robot interaction (HRI). We accomplish this task in a two step approach. First, we focus on the estimation of the head pose from …

Continue reading

Towards automatic learning of gait signatures for people identification in video

Seminar by Manuel J. Marin-Jimenez, Universidad de Córdoba Tuesday 19 December 2017, 11:00 – 12:00, room F107 INRIA Montbonnot Saint-Martin Abstract: This talk targets people identification in video based on the way they walk (i.e. gait). While classical methods typically derive gait signatures from sequences of binary silhouettes, in this talk we present the use …

Continue reading