Recurrent Mixture Density Network for Spatiotemporal Visual Attention

Understand

In many computer vision tasks, the relevant information to solve the problem at hand is mixed to irrelevant, distracting information.

• This has motivated researchers to design attentional models that can dynamically focus on parts of images or videos that are salient, e.g., by down-weighting irrelevant pixels.
• In this work, we propose a spatiotemporal attentional model that learns where to look in a video directly from human fixation data.
• We model visual attention with a mixture of Gaussians at each frame.