Papers › Naver at ActivityNet Challenge 2019 -- Task B Active Speaker Detection (AVA)
Naver at ActivityNet Challenge 2019 -- Task B Active Speaker Detection (AVA)
Joon Son Chung
This report describes our submission to the ActivityNet Challenge at CVPR 2019. We use a 3D convolutional neural network (CNN) based front-end and an ensemble of temporal convolution and LSTM classifiers to predict whether a visible person is speaking or not. Our results show significant improvements over the baseline on the AVA-ActiveSpeaker dataset.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Audio-Visual Active Speaker Detection | AVA-ActiveSpeaker | VGG-{LSTM+TCN} (ensemble) | validation mean average precision | 87.8% | #17 of 20 | Archive leaderboard | report |
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