1e.g., https://youtu.be/0ORaAnJYROg
2Project page: https://grail.cs.washington.edu/projects/

humannerf/

Given a single video of a human performing an activ-
ity, e.g., a YouTube or TikTok video of a dancer, we would
like the ability to pause at any frame and rotate 360 degrees
around the performer to view them from any angle at that
moment in time (Figure 1). This problem – free-viwepoint
rendering of a moving subject – is a longstanding research
challenge, as it involves synthesizing previously unseen
camera views while accounting for cloth folds, hair move-
ment, and complex body poses [5, 6, 15, 18, 27, 38, 59, 65].
The problem is particularly hard for the case of “in-the-
wild” videos taken with a single camera (monocular video),
the case we address in this paper.
HumanNeRF- Free-viewpoint Rendering of Moving People from Monocular Video