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TöRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis
[article]
2021
arXiv
pre-print
Neural networks can represent and accurately reconstruct radiance fields for static 3D scenes (e.g., NeRF). Several works extend these to dynamic scenes captured with monocular video, with promising performance. However, the monocular setting is known to be an under-constrained problem, and so methods rely on data-driven priors for reconstructing dynamic content. We replace these priors with measurements from a time-of-flight (ToF) camera, and introduce a neural representation based on an image
arXiv:2109.15271v2
fatcat:bxm73ltkobaivjrxc4yv2izsoy