AI Technology & Industry Review
In the new paper Compressing Volumetric Radiance Fields to 1 MB, an Alibaba Group research team proposes vector quantized radiance fields (VQRF), a simple yet efficient framework for compressing volumetric radiance fields that achieves up to 100x storage reduction, reducing original grid model size to around 1 MB with negligible loss on rendering quality.
In the new paper Is Attention All NeRF Needs?, a research team from the Indian Institute of Technology Madras and the University of Texas at Austin proposes Generalizable NeRF Transformer (GNT), a pure and universal transformer-based architecture for efficient on-the-fly reconstruction of NeRFs. The work demonstrates that a pure attention mechanism suffices for learning a physically-grounded rendering process.
In a paper currently under double-blind review for ICLR 2022, researchers propose StyleNeRF, a 3D-aware generative model that can synthesize high-resolution images at interactive rates while preserving high-quality 3D consistency, and can even generalize to unseen views with control on styles and poses.