The broken images to me look like instances where two or more cameras or images were used and then stitched together. Probably also done while the camera and object are moving making it more likely to be wonky.
No way. The letters/writing look exactly like mirrored GAN output. That's not what would happen with blur or stitching together (there would be no mirroring symmetry or all the '8' letters), or with synthetic 'machine teaching' datapoints either (as far as I've ever seen). Look at the cat StyleGAN sometime if you don't know what I'm talking about.
Which leaves me wonder what the point is. If you are generating GAN images per CIFAR or ImageNet class, you know what the label is and don't need to label it. Perhaps they just generate lots of images to fill up the pipeline for the CAPTCHAs, to avoid reuse which could be exploited by spammers, when they have too little paying work?
Which leaves me wonder what the point is. If you are generating GAN images per CIFAR or ImageNet class, you know what the label is and don't need to label it. Perhaps they just generate lots of images to fill up the pipeline for the CAPTCHAs, to avoid reuse which could be exploited by spammers, when they have too little paying work?