A unified deep sparse graph attention network for scene graph generation
Abstract
Scene graph generation (SGG) plays an important role in deep understanding of the visual scene. Despite the empirical success of traditional methods in many applications, they still have several challenges in the high computational complexity of dense graph and the inaccurate pruning of sparse graph. To tackle these problems, we propose a novel deep sparse graph attention network to mine the rich contextual clues and simultaneously preserve the...
Paper Details
Title
A unified deep sparse graph attention network for scene graph generation
Published Date
Mar 1, 2022
Journal
Volume
123
Pages
108367 - 108367
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