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11 to 20 of 12,402 Results
ZIP Archive - 560.7 MB - MD5: a5cb964adaa990edcdec393fa79a31a6
Jun 10, 2025
Rudnev, Viktor; Elgharib, Mohamed; Theobalt, Christian; Golyanik, Vladislav, 2025, "EventNeRF: Neural Radiance Fields from a Single Colour Event Camera", https://doi.org/10.17617/3.FCVXVU, Edmond, V1
Asynchronously operating event cameras find many applications due to their high dynamic range, no motion blur, low latency and low data bandwidth. The field has seen remarkable progress during the last few years, and existing event-based 3D reconstruction approaches recover sparse point clouds of the scene. However, such sparsity is a limiting fact...
ZIP Archive - 364.8 MB - MD5: 149952b6a67e33b7d0501a9cd35774a7
Gzip Archive - 18.0 GB - MD5: 1525db3826639a38bea1f1de6a0d4c2b
ZIP Archive - 229.0 MB - MD5: ec0c60dd6f0f37304ec059dbe7f5ffec
ZIP Archive - 132.2 MB - MD5: 8262660dd4b1d33a2b3322f2b5c20647
Jun 7, 2025
Rudnev, Viktor; Fox, Gereon; Elgharib, Mohamed; Theobalt, Christian; Golyanik, Vladislav, 2025, "Dynamic EventNeRF: Reconstructing General Dynamic Scenes from Multi-view RGB and Event Streams", https://doi.org/10.17617/3.AD2LQB, Edmond, V1
Volumetric reconstruction of dynamic scenes is an important problem in computer vision. It is especially challenging in poor lighting and with fast motion. This is partly due to limitations of RGB cameras: To capture frames under low lighting, the exposure time needs to be increased, which leads to more motion blur. In contrast, event cameras, whic...
XZ Archive - 8.7 GB - MD5: b6bbbcf139d0deb093ec524e1b40b6ba
Processed real data
XZ Archive - 1.8 GB - MD5: 28c32e09cb25dc530192ce570788c9d3
Synthetic scenes
XZ Archive - 66.9 GB - MD5: 3e81033e599593a5afd63277cb3e301e
Raw performance and calibration recordings
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