  In this technical report, we describe our solution to temporal action
proposal (task 1) in ActivityNet Challenge 2019. First, we fine-tune a
ResNet-50-C3D CNN on ActivityNet v1.3 based on Kinetics pretrained model to
extract snippet-level video representations and then we design a Relation-Aware
Pyramid Network (RapNet) to generate temporal multiscale proposals with
confidence score. After that, we employ a two-stage snippet-level boundary
adjustment scheme to re-rank the order of generated proposals. Ensemble methods
are also been used to improve the performance of our solution, which helps us
achieve 2nd place.
