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Found 2 papers, 0 papers with code
Shuffled Multi-Channel Sparse Signal Recovery
Assuming that we have a sensing matrix for the underlying signals, we show that the problem is equivalent to a structured unlabeled sensing problem, and establish sufficient conditions for unique recovery.
Representation Learning on Visual-Symbolic Graphs for Video Understanding
To capture this rich visual and semantic context, we propose using two graphs: (1) an attributed spatio-temporal visual graph whose nodes correspond to actors and objects and whose edges encode different types of interactions, and (2) a symbolic graph that models semantic relationships.
Ranked #10 on
Action Detection
on Charades
(using extra training data)
