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Found 5 papers, 0 papers with code
Deep Unsupervised Active Learning on Learnable Graphs
To make the learnt graph structure more stable and effective, we take into account $k$-nearest neighbor graph as a priori, and learn a relation propagation graph structure.
Action Shuffling for Weakly Supervised Temporal Localization
Weakly supervised action localization is a challenging task with extensive applications, which aims to identify actions and the corresponding temporal intervals with only video-level annotations available.
Tensor Power Iteration for Multi-Graph Matching
Due to its wide range of applications, matching between two graphs has been extensively studied and remains an active topic.
Multi-target Tracking with Motion Context in Tensor Power Iteration
In this paper, we model interactions between neighbor targets by pair-wise motion context, and further encode such context into the global association optimization.
Multi-target Tracking by Rank-1 Tensor Approximation
In this paper we formulate multi-target tracking (MTT) as a rank-1 tensor approximation problem and propose an 1 norm tensor power iteration solution.
