CBR-Net: Cascade Boundary Refinement Network for Action Detection: Submission to ActivityNet Challenge 2020 (Task 1)

Understand

In this report, we present our solution for the task of temporal action localization (detection) (task 1) in ActivityNet Challenge 2020.

• The purpose of this task is to temporally localize intervals where actions of interest occur and predict the action categories in a long untrimmed video.
• Our solution mainly includes three components: 1) feature encoding: we apply three kinds of backbones, including TSN [7], Slowfast[3] and I3d[1], which are both pretrained on Kinetics dataset[2].
• Applying these models, we can extract snippet-level video representations; 2) proposal generation: we choose BMN [5] as our baseline, base on which we design a Cascade Boundary Refinement Network (CBR-Net) to conduct proposal detection.