3 accepted papers
Resource-efficient audio-visual fusion techniques often struggle to maintain robust performance across varying acoustic noise conditions in speech recognition tasks. This paper introduces a dynamic routing approach for noise-robust audio-visual fusion, which adaptively directs features to noise-spec…
We present a novel resource-efficient end-to-end architecture for lipreading that achieves state-of-the-art results on a popular and challenging benchmark. In particular, we make the following contributions: First, inspired by the recent success of the EfficientNet architecture in image classificati…
The goal of our work is to complete missing areas of images of talking faces, exploiting information from both the visual and audio modalities. Existing image inpainting methods rely solely on visual content that doesn't always provide sufficient information for the task. To counter this, we propose…