Complex Sequential Understanding through the Awareness of Spatial and Temporal Concepts

30 May 2020 Bo Pang Kaiwen Zha Hanwen Cao Jiajun Tang Minghui Yu Cewu Lu

Understanding sequential information is a fundamental task for artificial intelligence. Current neural networks attempt to learn spatial and temporal information as a whole, limited their abilities to represent large scale spatial representations over long-range sequences... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet