Action Spotting using Dense Detection Anchors Revisited: Submission to the SoccerNet Challenge 2022

This technical report describes our submission to the Action Spotting SoccerNet Challenge 2022. The challenge is part of the CVPR 2022 ActivityNet Workshop. Our submission is based on a method that we proposed recently, which focuses on increasing temporal precision via a densely sampled set of detection anchors. Due to its emphasis on temporal precision, this approach is able to produce competitive results on the tight average-mAP metric, which uses small temporal evaluation tolerances. This recently proposed metric is the evaluation criterion used for the challenge. In order to further improve results, here we introduce small changes in the pre- and post-processing steps, and also combine different input feature types via late fusion. This report describes the resulting overall approach, focusing on the modifications introduced. We also describe the training procedures used, and present our results.