Papers by Shaoxiang Wu

1 papers
Denoising Bottleneck with Mutual Information Maximization for Video Multimodal Fusion (2023.acl-long)

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Challenge: Prior denoising methods suppress redundant and noisy information at risk of losing critical information.
Approach: They propose a denoising bottleneck fusion model for fine-grained video multimodal fusion . they employ a bottleneck mechanism to filter out noise and redundancy with a restrained receptive field .
Outcome: The proposed model improves on state-of-the-art video multimodal fusion benchmarks.

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