the video. “There are two observations that are used here,” Arushi adds. “One is that element segments do not overlap with other segments in the video, in the same video, and that each element segment would be a continuous sequence of clips. So that means that the queries should focus on different parts of the video from one another for the same video, and the query should also focus on a continuous sequence of clips when cross attention is performed in the decoder, the transformer decoder. This is the implicit segmentation regularization!” Does this research open new directions, or may it be made more powerful by further studies? Arushi thinks so: this work has been limited by the lack of annotations. So probably the rubric adherence ability could be improved by using annotations regarding like the rubric breakdown for each performance, for each element. Arushi will tell you more about this computer vision work when you visit her poster, today (Monday) at Poster Session 5, between 16:15 and 18:00. DAILY WACV Monday Rubric-Constrained Figure Skating Scoring 17
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