11 citations · 23 across the 8 of their papers we have counts for
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cs.CV2021★ 11 cited
Learning Neural Light Fields with Ray-Space Embedding Networks
Benjamin Attal, Jia-Bin Huang, Michael Zollhoefer +2
Neural radiance fields (NeRFs) produce state-of-the-art view synthesis results. However, they are slow to render, requiring hundreds of network evaluations per pixel to approximate…
cs.CV2021★ 10 cited
TöRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis
Benjamin Attal, Eliot Laidlaw, Aaron Gokaslan +4
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 vid…