S. Escalera

Publications
Influence

ChaLearn Looking at People RGB-D Isolated and Continuous Datasets for Gesture Recognition

Jun Wan, S. Li, Y. Zhao, Shuai Zhou, I. Guyon, S. Escalera
Computer Science
IEEE Conference on Computer Vision and Pattern…
1 June 2016

In this paper, we present two large video multi-modal datasets for RGB and RGB-D gesture recognition. Expand

ChaLearn Looking at People Challenge 2014: Dataset and Results

S. Escalera, X. Baró, +7 authors I. Guyon
Computer Science
ECCV Workshops
6 September 2014

This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. Expand

On the Decoding Process in Ternary Error-Correcting Output Codes

S. Escalera, O. Pujol, P. Radeva
Computer Science, Medicine
IEEE Transactions on Pattern Analysis and Machine…
2010

We present a taxonomy that embeds all binary and ternary ECOC decoding strategies into four groups. Expand

ChaLearn Looking at People 2015: Apparent Age and Cultural Event Recognition Datasets and Results

S. Escalera, Junior Fabian, +6 authors I. Guyon
Computer Science, Psychology
IEEE International Conference on Computer Vision…
7 December 2015

We ran two new competitions within the field of Looking at People: (1) age estimation and (2) cultural event recognition, both in still images. Expand

ChaLearn LAP 2016: First Round Challenge on First Impressions - Dataset and Results

Víctor Ponce-López, B. Chen, +6 authors S. Escalera
Computer Science
ECCV Workshops
8 October 2016

This paper summarizes the ChaLearn Looking at People 2016 First Impressions challenge data and results obtained by the teams in the first round of the competition. Expand

Multi-modal gesture recognition challenge 2013: dataset and results

S. Escalera, J. González, +5 authors H. Escalante
Computer Science
ICMI '13
9 December 2013

The recognition of continuous natural gestures is a complex and challenging problem due to the multi-modal nature of involved visual cues (e.g. fingers and lips movements, subtle facial expressions, body pose, etc.), as well as technical limitations such as spatial and temporal resolution and unreliable depth cues. Expand

ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016

S. Escalera, M. Torres, +8 authors M. Valstar
Computer Science
IEEE Conference on Computer Vision and Pattern…
19 December 2016

We present the 2016 ChaLearn Looking at People and Faces of the World Challenge and Workshop, which ran three competitions on the common theme of face analysis from still images. Expand

Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification

X. Baró, S. Escalera, Jordi Vitrià, O. Pujol, P. Radeva
Engineering, Computer Science
IEEE Transactions on Intelligent Transportation…
1 March 2009

The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. Expand

An incremental node embedding technique for error correcting output codes

O. Pujol, S. Escalera, P. Radeva
Computer Science
Pattern Recognit.
1 February 2008

In this paper, we present a novel approach that improves the performance of any initial output coding by extending it in a sub-optimal way. Expand

A Dataset and Benchmark for Large-Scale Multi-Modal Face Anti-Spoofing

Shifeng Zhang, Xiaobo Wang, +6 authors S. Li
Computer Science
IEEE/CVF Conference on Computer Vision and…
2 December 2018

We introduce a large-scale multi-modal face anti-spoofing dataset, namely CASIA-SURF, which consists of 1,000 subjects with 21,000 videos and each sample has 3 modalities (RGB, Depth, IR). Expand

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