Idan Harel

I'd also add that if it's not apparent from the plots, both models are under-predicting. sometimes by 20 years margin. It's getting worse as the age increases. I can plot...

@yu4u thank you! I was surprised as well from the results so I posted here to get your feedback, and I applied your suggestions (regrading argmax, I don't know why...

Hey, some more updates.. To verify on which age groups the IMDB model is mostly wrong on his current iteration (after above fixes) I did the following: For each prediction,...

@yu4u oh. That explains UTK results on >60 but not at

@yu4u I think that's part of the issue but since age group 18-40 gave me 80% accuracy +-17years I think that there's still some digging left to be done..

@yu4u When you say train and then finetune, do you mean train again with prior weights? Unfortunately I don't have the resources to train those model.. If I can be...

Thank you for your suggestions, I tried augmenting the images, applying affine transformations (scaling, rotating, translation), for each image I've created 50 copies, where one if the original and the...

Adding some interesting results, for age groups (0,2), (4,6), (8,13), (15,20), (25,32), (38,43), (48,53), (60, 99) described in https://arxiv.org/pdf/1710.02985.pdf (DeX, p10), on IMDB pretrained model validated with appa-real on apparent...

@yu4u thanks for sharing! Yes of course, I'm using imgaug for augmentation and so using Fliplr(.5) and affine translate_percent={"x": (-.1, .1), "y": (-.1, .1)} which by Keras definition if I...

I think training on 128x128 would also boost accuracy a bit. Unfortunately this is something that could take me about a month (already tried doing so on my machine) and...