The Establishment of a precise intelligent evaluation system for sports events: Diving.

The introduction of action quality assessment technology in sports events to achieve precise intelligent evaluation can greatly enhance the objectivity and effectiveness of competition results. Taking diving as the specific application background, this study proposes a novel Multi-granularity Extraction Approach for Temporal-spatial features in judge scoring prediction (MEAT) under the conditions of action quality assessment. On the one hand, it uses dual-modal inflated 3D ConvNet to extract the temporal and spatial features of each modal diving video at the video granularity parallelly and to merge them to form a global feature.