A research team from NVIDIA presented new deep learning based system which is capable of creating decent-looking fake slow motion only through post processing. They claim their software can generate the in-between frames in a more convincing way than any other existing solution. Example of the Resulting Slow Motion Footage. Source: NVIDIA The idea of creating “fake” slow motion in post production is not new. Computers can generate frames artifically in between existing frames and therefore increase the resulting framerate of the footage. Normal NLEs do this through simple frame blending (whereas Final Cut Pro X seems to do it better than Premiere Pro CC still). However, the existing market-leading solution is a special piece of software from RE:Vision Effects called Twixtor– which however gives nice results only under perfect circumstances. For example, on a simple moving object on an even background. As soon as there is a complex very fast movement and/or uneven background included, the resulting frames are not convincing and objects are falling apart. Researchers from NVIDIA developed a new system based on deep learning which can produce better results. They aim to present their work at the upcoming annual Computer Vision and Pattern Recognition (CVPR) conference on June 21st in Salt Lake City, Utah. The team achieved the results by using NVIDIA Tesla V100 GPUs and cuDNN-accelerated deep learning framework. Scientists trained the system on over 11,000 videos of everyday and sports activities shot natively at 240 frames-per-second. Once trained, the convolutional neural network was able to predict the...
Published By: CineD - Wednesday, 20 June, 2018