In anticipation of the Intl. Conf. on Computer Vision (#ICCV2021) this week, I rounded up all papers that use Neural Radiance Fields (NeRFs) represented in the main #ICCV2021 conference here (1/N):
dellaert.github.io/NeRF21 Many of the papers I discussed in my original blog-post on NerF (dellaert.github.io/NeRF/) made it into CVPR, but the sheer number of NeRF-style papers that appeared on Arxiv this year meant I could no longer keep up. 2/N

2020 was the year in which *neural volume rendering* exploded onto the scene, triggered by the impressive NeRF paper by Mildenhall et al. I wrote a post as a way of getting up to speed in a fascinating and very young field and share my journey with you: dellaert.github.io/NeRF/ The precursors to NeRF are approaches that use an *implicit* surface representation. At CVPR 2019, 3 papers introduced the use of neural nets as *scalar function approximators* to define occupancy and/or signed distance functions.

How about giving all conference submissions one extra page but insisting we use verbose citations, like (Mildenhall et al. 2020). I find myself constantly flipping to the references page.