Publication: E-NeRF: Neural Radiance Fields From a Moving Event Camera
E-NeRF: Neural Radiance Fields From a Moving Event Camera
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Klenk, S., Koestler, L., Scaramuzza, D., & Cremers, D. (2023). E-NeRF: Neural Radiance Fields From a Moving Event Camera. IEEE Robotics and Automation Letters, 8(3), 1587–1594. https://doi.org/10.1109/LRA.2023.3240646
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Estimating neural radiance fields (NeRFs) from “ideal” images has been extensively studied in the computer vision community. Most approaches assume optimal illumination and slow camera motion. These assumptions are often violated in robotic applications, where images may contain motion blur, and the scene may not have suitable illumination. This can cause significant problems for downstream tasks such as navigation, inspection, or visualization of the scene. To alleviate these problems, we present E-NeRF, the first method which estima
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- Klenk, Simon
- Koestler, Lukas
- Scaramuzza, Davide
- Cremers, Daniel
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Klenk, S., Koestler, L., Scaramuzza, D., & Cremers, D. (2023). E-NeRF: Neural Radiance Fields From a Moving Event Camera. IEEE Robotics and Automation Letters, 8(3), 1587–1594. https://doi.org/10.1109/LRA.2023.3240646
