[CVPR 2022] Motion-from-Blur: 3D Shape and Motion Estimation of Motion-blurred Objects in Videos

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Prerequisites

Kaolin is available here: https://github.com/NVIDIAGameWorks/kaolin Pre-trained DeFMO is implemented directly in kornia.feature.DeFMO

Running

The code can be easily run by 'python run.py --input video.avi', e.g. check run.sh script. The results will be written to the output folder.

To run on the fast moving object deblurring benchmark, we used: https://github.com/rozumden/fmo-deblurring-benchmark For synthetic dataset generation, we used the publicly available implementation from DeFMO authors: https://github.com/rozumden/DeFMO/tree/master/renderer

Reference

If you use this repository, please cite the following publication:

@inproceedings{mfb,
  title = {Motion-from-Blur: 3D Shape and Motion Estimation of Motion-blurred Objects in Videos},
  author = {Denys Rozumnyi and Martin R. Oswald and Vittorio Ferrari and Marc Pollefeys},
  booktitle = {CVPR},
  month = {Jun},
  year = {2022}
}