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ChaLearn Looking at People RGB-D Isolated and Continuous Datasets for Gesture Recognition
TLDR
In this paper, we present two large video multi-modal datasets for RGB and RGB-D gesture recognition. Expand
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ChaLearn Looking at People Challenge 2014: Dataset and Results
TLDR
This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. Expand
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On the Decoding Process in Ternary Error-Correcting Output Codes
TLDR
We present a taxonomy that embeds all binary and ternary ECOC decoding strategies into four groups. Expand
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ChaLearn Looking at People 2015: Apparent Age and Cultural Event Recognition Datasets and Results
TLDR
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
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ChaLearn LAP 2016: First Round Challenge on First Impressions - Dataset and Results
TLDR
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
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Multi-modal gesture recognition challenge 2013: dataset and results
TLDR
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
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ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016
TLDR
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
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Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification
TLDR
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
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An incremental node embedding technique for error correcting output codes
TLDR
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
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A Dataset and Benchmark for Large-Scale Multi-Modal Face Anti-Spoofing
TLDR
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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