2 citations · 3 across the 8 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.CV2024
Extreme Compression of Adaptive Neural Images
Leo Hoshikawa, Marcos V. Conde, Takeshi Ohashi +1
Implicit Neural Representations (INRs) and Neural Fields are a novel paradigm for signal representation, from images and audio to 3D scenes and videos. The fundamental idea is to r…
cs.CV2024
Mixed-precision Supernet Training from Vision Foundation Models using Low Rank Adapter
Yuiko Sakuma, Masakazu Yoshimura, Junji Otsuka +2
Compression of large and performant vision foundation models (VFMs) into arbitrary bit-wise operations (BitOPs) allows their deployment on various hardware. We propose to fine-tune…