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AVA-Kinetics Challenge 2020

The third AVA challenge ran as part of the International Challenge on Activity Recognition (ActivityNet) workshop at CVPR 2020. It included two tasks: action detection using the newly-released AVA-Kinetics dataset, and active speaker detection using AVA ActiveSpeaker.

The competition led to another significant improvement (+5.4 mAP) in action detection performance. A video presenting the results, including presentations by the winners of the action and active speaker tasks, can be found on YouTube as well as on bilibili.

Thanks as always to everyone who entered, and congratulations to the winners! Details of the winning methods are available in the reports below.

AVA Actions

Rank Team Name Entry Report mAP
1 CUHK-SenseTime Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization 39.62
2 ByteDance & Shanghai Jiao Tong University Multiple Attempts for AVA-Kinetics 32.91
3 Fujitsu Multi-scale Spatiotemporal Features for Action Localization 31.88

AVA Active Speaker

Rank Team Name Entry Report mAP
1 Universidad de los Andes Active Speaker Detection 86.68

AVA Challenge 2019

The second AVA Challenge was held at the International Challenge on Activity Recognition (ActvityNet) workshop in conjunction with CVPR 2019. In addition to the spatio-tempral action recognition task, this year we introduced a new secondary task: active speaker detection.

Thank you to all who participated! A total of 30 teams entered, making a combined 79 submissions, achieving an impressive +13 mAP increase over last year's winner for the Actions task, and establishing a new, strong baseline for the Active Speaker task.

The winners of the challenge are below. You will be able to find the full leaderboard at the ActivityNet Challenge site.

AVA Actions

Rank Team Name Entry Report mAP
1 FAIR SlowFast Networks for Video Recognition 34.25
2 Machine Vision and Intelligence Group, Shanghai Jiao Tong University Three Branches: Detecting Actions with Richer Features 32.49
3 Shanghai Jiao Tong University & ByteDance AI Lab ByteDance AI Lab AVA Challenge 2019 Technical Report 30.20

AVA Active Speaker

Rank Team Name Entry Report mAP
1 Naver Corporation Naver at ActivityNet Challenge 2019 87.82
2 University of Chinese Academy of Sciences Multi Task Learning for Audio Visual Active Speaker Detection 83.49
- Google baseline AVA-ActiveSpeaker: An Audio-Visual Dataset for Active Speaker Detection 82.08


AVA Challenge 2018

The first AVA challenge was held in partnership with the ActivityNet workshop at CVPR 2018. Details on the specific task can be found here.

A total of 16 teams entered, making a combined 35 submissions, and achieving a +5.5 point increase in mAP over the baseline.

The winners of the challenge are below. You can find the full leaderboard at the ActivityNet Challenge site.

Rank Team Name Entry Report Task 1 mAP Task 2 mAP
1 Tsinghua/Megvii Human Centric Spatio-Temporal Action Localization 21.08 20.99
2 DeepMind A Better Baseline for AVA 21.03 21.03
3 YH Technologies YH Technologies at ActivityNet Challenge 2018 19.60 19.60

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