# 1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

arXiv: https://arxiv.org/abs/2006.09116 · HTML: https://mlsanity.com/paper/2006.09116/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jun 2020.

## Built on by (most cited first, 2 of 2)

- [Beyond Transfer Learning: Co-finetuning for Action Localisation](https://mlsanity.com/paper/2207.03807/) (2022)
- [Towards Large-scale Masked Face Recognition](https://mlsanity.com/paper/2310.16364/) (2023)

## Abstract (arXiv)

This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020. Our entry is mainly based on Actor-Context-Actor Relation Network. We describe technical details for the new AVA-Kinetics dataset, together with some experimental results. Without any bells and whistles, we achieved 39.62 mAP on the test set of AVA-Kinetics, which outperforms other entries by a large margin. Code will be available at: https://github.com/Siyu-C/ACAR-Net.