Realtime Video Enhancement via Deep Learning

Hello Nvidia,

Your work has greatly inspired me, and I truly appreciate your assistance.

Currently, I am using a camera capable of 500fps at a resolution of 800x600 to detect tennis balls. To prevent motion blur, I need to maintain a high shutter speed. However, capturing at 500 fps results in dark images, and utilizing image processing techniques introduces noise into the images.

I am in search of a deep learning pipeline that could mitigate these issues. Do you offer an end-to-end video enhancement pipeline? Additionally, I would like to know if Nvidia provides an optimized toolkit for video enhancement, such as super-resolution or low-light enhancement.

Thank you for your support.

Below are taken with 500fps and 20 fps respectively.


Seems the exposure time is too short for the camera to capture a human visible image when you set the camera with 500 FPS.

I can see the ball in the picture taken with 500 FPS even it is too dark to be identified. Are you asking for a model which can improve the picture’s quality?

The goal is to detect the ball (all four balls in the dark images). What model would you recommend?
(If improving the picture’s quality helps the detection, I would appreciate if a suitable model exists)

Unfortunately there is no such model provided by TAO toolkit. You may need to search some image quality improvement algorithm or models by yourself.