I'm a professional neuroscientist that specializes in vision research with a computational bent. They used all the main stream, state of the art, openly available object recognition algorithms currently in use. Computer vision is a huge market, with many applications, from the DoD to self-driving cars to image-based searches. I doubt some 5-figure prize is going to out perform the best algorithms several distinct industries and academia have managed to create while being funded to the tune of over a billion a year for the last 10 years or so.
These are serious researchers. If you think you think you can get any type of computer vision that significantly outperforms humans on this type of task, there is a unicorn startup and multiple ultra-high profile publications awaiting you.
And just FYI based on your further post: they used two types of convolutional neural nets (see Methods: Model Versions and Parameters).