Nvidia showcases AI Slow Motion Video Conversion Tech

One of Nvidia’s fastest growing markets is in the machine learning category, where their Tesla V100 series GPUs are utilising their purpose-built tensor cores to accelerate a large number of deep learning workloads, accelerating AI training and development to create compelling new technologies. 

Nvidia’s research arm has created a deep learning system which can create high-quality slow-motion videos using standard 30FPS footage, creating a reasonably accurate approximation of real-like slow-motion video without the need for specialised equipment. 

Using their AI-focused Tesla V100 GPUs and a  cuDNN-accelerated PyTorch deep learning framework, Nvidia trained their system to predict extra frames for video content, allowing low framerate footage to be given extra fluidity and for slow-motion footage to be made even slower, up to four times slower. 

This technology can create multiple intermediate frames, allowing footage to become several times more fluid when played back side-by-side. Nvidia has stated that they used 11,000 240FPS videos to train their AI, allowing it to create approximate extra detail in low framerate footage for extra fluidity.