Stochastic prediction of multi-agent interactions from partial observations
We present a method that learns to integrate temporal information, from a learned dynamics model, with ambiguous visual information, from a learned vision model, in the context of interacting agents. Our method is based on a graph-structured variational recurrent neural network (Graph-VRNN), which i...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
International Conference on Learning Representations
2020
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| Online Access: | https://hdl.handle.net/1721.1/126593 |