This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. The competition was split into three independent tracks: human pose recovery from RGB data, action and interaction recognition from RGB data sequences, and multi-modal gesture recognition from RGB-Depth sequences. For all the tracks, the goal was to perform user-independent rec...

To evaluate state-of-the-art algorithms and draw new insights regarding potential future research directions in distant speech recognition, Kinoshita et al. [1] launched the REverberant Voice Enhancement and Recognition Benchmark Challenge, commonly known as the REVERB Challenge, intended to provide a test bed for researchers to evaluate their methods based on common corpora and evaluation metr...

This session features exciting keynote speeches by Rajeev Madhavan (Chairman & CEO, Magma Design Automation), Michael Reinhardt (CEO & President, RubiCAD), and Shekhar Borker (Intel Fellow & Director of Circuit Research Lab). In the first keynote speech, titled “Addressing the IC Designer’s Needs: Integrated Design Software for Faster, More Economical Chip Design”, Rajeev Madhaven highlights th...

Crowdsourced demarcations of object boundaries in images (segmentations) are important for many vision-based applications. A commonly reported challenge is that a large percentage of crowd results are discarded due to concerns about quality. We conducted three studies to examine (1) how does the quality of crowdsourced segmentations differ for familiar everyday images versus unfamiliar biomedic...

Abstract. For making the web of linked data grow, information extraction methods are a good alternative to manual dataset curation, since there is an abundance of semi-structured and unstructured information which can be harvested that way. At the same time, existing Linked Data sets can be used for training and evaluating such information extraction systems. In this paper, we introduce the Lin...

The Grid-Based Path Planning Competition has just completed its third iteration. The entries used in the competition have improved significantly during this time, changing the view of the state of the art of gridbased pathfinding. Furthermore, the entries from the competition have been made publicly available, improving the ability of researchers to compare their work. This paper summarizes the...

The 2014 edition of the Linked Data Mining Challenge, conducted in conjunction with Know@LOD 2014, has been the third edition of this challenge. The underlying data came from two domains: public procurement, and researcher collaboration. Like in the previous year, when the challenge was held at the Data Mining on Linked Data workshop co-located with the European Conference on Machine Learning a...