"Photo Rater: Photographs Auto-Selector with Deep Learning. (arXiv:2211.14420v1 [cs.CV])" β€” Have a lot of photos and are too lazy to rate them yourself? Well, never fear, Machine Learning is here πŸ˜›

This system rates images based on machine learning. Being naturally lazy, I think I'd want this ...

Paper: http://arxiv.org/abs/2211.14420

No code/ demo

#AI #CV #NewPaper #DeepLearning #MachineLearning

Photo Rater: Photographs Auto-Selector with Deep Learning

Photo Rater is a computer vision project that uses neural networks to help photographers select the best photo among those that are taken based on the same scene. This process is usually referred to as "culling" in photography, and it can be tedious and time-consuming if done manually. Photo Rater utilizes three separate neural networks to complete such a task: one for general image quality assessment, one for classifying whether the photo is blurry (either due to unsteady hands or out-of-focusness), and one for assessing general aesthetics (including the composition of the photo, among others). After feeding the image through each neural network, Photo Rater outputs a final score for each image, ranking them based on this score and presenting it to the user.

arXiv.org
@f Having something like this to detect blurry pics would really speed up a wildlife photography workflow
@ahdchild Yes! Reading some of these papers, I immediately see a practical application. Too bad that a lot of them don’t have code since I’d really like to try it out now even if it means that I have to adapt the code to the task myself πŸ™‚