Using Convolutional 3D Neural Networks for User-independent continuous gesture recognition
By Necati Cihan Camgöz, Simon Hadfield, Oscar Koller, Richard Bowden. 2016
98 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Human-Computer Interaction
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Pichao Wang
- Wanqing Li
- Philip O. Ogunbona
- Zhimin Gao
- Chang-Fu Tang
- Hanqing Lu
- Yifan Zhang
- Jian Cheng
In Computer Vision and Pattern Recognition
In Human-Computer Interaction
- Pichao Wang
- Philip O. Ogunbona
- Wanqing Li
- Zhimin Gao
- Chang-Fu Tang
- Yifan Zhang
- Jian Cheng
- Hanqing Lu
Citations in the corpus
- Depth Pooling Based Large-Scale 3-D Action Recognition With Convolutional Neural Networks (2018, methodology): “C3D [59] applied 3D convolutional networks to RGB video and jointly”
- Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks (2016, unknown): “286915 2 TARDIS [40] 0.”
- Two streams Recurrent Neural Networks for Large-Scale Continuous Gesture Recognition (2016, methodology): “The other two teams, TARDIS [36] and AMRL [37], adopted the method of 3D Convolutional Neural Networks and obtained similar”
- EgoGesture: A New Dataset and Benchmark for Egocentric Hand Gesture Recognition (2018, methodology): “The classifier is trained with an extra non-gesture class to handle the non-gesture part [41].”
- MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language (2018, unknown): “showed large improvements embedding 2D-CNNs in HMMs [36, 37], related works with 3D-CNNs exist [29, 6].”
- MMTM: Multimodal Transfer Module for CNN Fusion (2019, background): “[38] present a late fusion approach for fusing the scores of unimodal 3D CNN streams.”