# 25 years of CNNs: Can we compare to human abstraction capabilities?

arXiv: https://arxiv.org/abs/1607.08366 · HTML: https://mlsanity.com/paper/1607.08366/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jul 2016.

## Built on by (most cited first, 10 of 10)

- [A Review of Emerging Research Directions in Abstract Visual Reasoning](https://mlsanity.com/paper/2202.10284/) (2022)
- [Understanding the computational demands underlying visual reasoning](https://mlsanity.com/paper/2108.03603/) (2021)
- [GAMR: A Guided Attention Model for (visual) Reasoning](https://mlsanity.com/paper/2206.04928/) (2022)
- [Solving the Same-Different Task with Convolutional Neural Networks](https://mlsanity.com/paper/2101.09129/) (2021)
- [Recurrent Vision Transformer for Solving Visual Reasoning Problems](https://mlsanity.com/paper/2111.14576/) (2021)
- [Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems](https://mlsanity.com/paper/2110.09947/) (2021)
- [Deep Neural Networks Can Learn Generalizable Same-Different Visual Relations](https://mlsanity.com/paper/2310.09612/) (2023)
- [Arguments for the Unsuitability of Convolutional Neural Networks for Non--Local Tasks](https://mlsanity.com/paper/2102.11944/) (2021)
- [Abutting Grating Illusion: Cognitive Challenge to Neural Network Models](https://mlsanity.com/paper/2208.03958/) (2022)
- [Convolutional Neural Networks Can (Meta-)Learn the Same-Different Relation](https://mlsanity.com/paper/2503.23212/) (2025)

## Abstract (arXiv)

We try to determine the progress made by convolutional neural networks over the past 25 years in classifying images into abstractc lasses. For this purpose we compare the performance of LeNet to that of GoogLeNet at classifying randomly generated images which are differentiated by an abstract property (e.g., one class contains two objects of the same size, the other class two objects of different sizes). Our results show that there is still work to do in order to solve vision problems humans are able to solve without much difficulty.