Video Primal Sketch: A Unified Middle-Level Representation for Video

Author:

Han Zhi,Xu Zongben,Zhu Song-Chun

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Geometry and Topology,Computer Vision and Pattern Recognition,Condensed Matter Physics,Modeling and Simulation,Statistics and Probability

Reference42 articles.

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3. Besag, J.: Spatial interactions and the statistical analysis of lattice systems. J. R. Stat. Soc. Ser. B 36, 192–236 (1974)

4. Black, M.J., Fleet, D.J.: Probabilistic detection and tracking of motion boundaries. IJCV 38(3), 231–245 (2000)

5. Bouthemy, P., Hardouin, C., Piriou, G., Yao, J.: Mixed-state auto-models and motion texture modeling. J. Math. Imaging Vis. 25(3) (2006)

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1. Learning Energy-Based Spatial-Temporal Generative ConvNets for Dynamic Patterns;IEEE Transactions on Pattern Analysis and Machine Intelligence;2021-02-01

2. Video sketch: A middle-level representation for action recognition;Applied Intelligence;2020-11-06

3. Synthesizing Dynamic Patterns by Spatial-Temporal Generative ConvNet;2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR);2017-07

4. Temporal Scale Selection in Time-Causal Scale Space;Journal of Mathematical Imaging and Vision;2017-01-03

5. Active Trace: A Sparse Spatiotemporal Representation for Videos;IEEE Access;2017

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