The problem is self-evident. Researchers care more about original ideas and less about designing visually appealing graphics. If you pick a random paper from any top ML-conference, most likely you will be faced with figures that would fail any design class.
There are rare exceptions, and these stand out.
On first read of your article, paper, or blog, one typically scrolls quickly through all pictures and tries to build a first impression on whether it is worth spending more time on. If you confuse the reader upfront with a paint-like figure, you diminish your chances of receiving the reader’s full attention.
During my paper writing, I faced the same problem and was searching for some online templates. However, nothing seemed to match my demands. So, I hunted down some well-crafted papers and assembled a package that would have been the solution I was looking for.
The templates now include:
- Most common symbols in machine learning architectures
- Consistent color scheme for model components
- Camera symbols for point cloud methods
- Blender shaders and geometric nodes to create presentable point clouds out of any mesh
Have a look at some examples below and feel free to give it a try yourself. All Illustrator templates and Blender file can be downloaded here and used both commercially and non-commercially without any license.
Reach out to me anytime if you have questions or think that something is missing.
Enjoy!
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