CORDIS Project
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This project focuses on developing Neural OmniVideo Models that enhance video analysis and synthesis by combining deep learning techniques with external model knowledge. It aims to create effective video representations and improve understanding of video dynamics, addressing challenges in processing complex video data.
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, apply…
WEIZMANN INSTITUTE OF SCIENCE
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