Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis

By Christian Thériault, Nicolas Thomé, Matthieu Cord. 2013

83 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Christoph Feichtenhofer
2. Luc Van Gool
3. Andrew Zisserman
4. Jitendra Malik
5. Axel Pinz
6. Richard P. Wildes
7. Cordelia Schmid
8. Abhinav Kumar Gupta

Citations in the corpus

• Bags of Spacetime Energies for Dynamic Scene Recognition (2014, methodology): “Here, systematic comparisons suggest that spatiotemporal orientations provide particularly strong primitives for dynamic scene recognition [6, 9].”
• Temporal Residual Networks for Dynamic Scene Recognition (2017, methodology): “Three of the evaluated algorithms, C3D [44], BoSE [11] and SFA [42], have shown the first, second and fourth best performance in previous dynamic scenes evaluations.”