Top1 Solution of QQ Browser 2021 Ai Algorithm Competition Track 1 : Multimodal Video Similarity
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Abstract (arXiv)
In this paper, we describe the solution to the QQ Browser 2021 Ai Algorithm Competition (AIAC) Track 1. We use the multi-modal transformer model for the video embedding extraction. In the pretrain phase, we train the model with three tasks, (1) Video Tag Classification (VTC), (2) Mask Language Modeling (MLM) and (3) Mask Frame Modeling (MFM). In the finetune phase, we train the model with video similarity based on rank normalized human labels. Our full pipeline, after ensembling several models, scores 0.852 on the leaderboard, which we achieved the 1st place in the competition. The source codes have been released at Github.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 7 of its 11 references that are in the map. First posted on arXiv 30 Oct 2021.
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References · 7
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- 2021Survey: Transformer based Video-Language Pre-trainingcited by 27
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