ERC Starting Grant · 2023
Neural OmniVideo: Fusing World Knowledge into Smart Video-Specific Models
The field of computer vision has made unprecedented progress in applying Deep Learning (DL) to images. Nevertheless, expanding this progress to videos is dramatically lagging behind, due to two key challenges: (i) video data is highly complex and diverse, requiring order of magnitude more training data than images, and (ii) raw video data is extremely high dimensional. These challenges make the processing of entire video pixel-volumes at scale prohibitively expensive and ineffective. Thus, applying DL at scale to video is restricted to short clips or aggressively sub-sampled videos. On the other side of the spectrum, video-specific models—a single or a few neural networks trained on a…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.