Noname manuscript No. (will be inserted by the editor) The ChaLearn Gesture Dataset (CGD 2011)

Citations in the corpus

RGB-D-based Human Motion Recognition with Deep Learning: A Survey (2017, background): “For example, Wan et al. [168] proposed the novel spatial-temporal features for one-shot learning gesture recognition and have got promising performances on Chalearn Gesture Dataset CGD) [169].”
ChaLearn looking at people: A review of events and resources (2017, unknown): “We split them into challenges and their associated workshops, special issues, and Challenges in Machine Learning (CIML) Springer book series.”
Multi-layered gesture recognition with Kinect (2015, methodology): “The ChaLearn Gesture Dataset (CGD 2011) (Guyon et al., 2014) is used in all experiments, which is designed for one-shot learning.”
Large-scale Isolated Gesture Recognition using Convolutional Neural Networks (2016, methodology): “[36] I. Guyon, V. Athitsos, P. Jangyodsuk, and H. J. Escalante, “The chalearn gesture dataset (CGD 2011),”Machine Vision and Applications, vol. 25, no. 8, pp. 1929–1951, 2014.”
Explore Efficient Local Features from RGB-D Data for One-Shot Learning Gesture Recognition (2016, background): “Those top 14 results are derived from [18].”
Large-scale gesture recognition with a fusion of RGB-D data based on the C3D model (2016, background): “which is derived from the CGD dataset [22].”
Challenges in multimodal gesture recognition (2016, methodology): “The datasets are described in details in a companion paper (Guyon et al., 2014).”
Depth Pooling Based Large-Scale 3-D Action Recognition With Convolutional Neural Networks (2018, methodology): “1) Description: The ChaLearn LAP ConGD Dataset is also derived from the ChaLearn Gesture Dataset (CGD) [51].”
Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks (2016, methodology): “The ChaLearn LAP ConGD Dataset is derived from the ChaLearn Gesture Dataset (CGD) [37].”
Multimodal Gesture Recognition Using 3-D Convolution and Convolutional LSTM (2017, methodology): “IsoGD [1] is a large-scale isolated gesture dataset which is derived from the ChaLearn Gesture Dataset (CGD) [41].”