karxxm
Joined 8 years ago
Joined 8 years ago
The volume rendering engine I have been working on uses a histogram for the value distribution, and on top of it, one can draw lines that indicate the opacity. Additionally, one can set colors to the control points, which are then linearly interpolated for the given ranges.
If you solve a problem that had been around for a while and LLMs offer a new way of approaching it, then it can definitely become a paper.
Of cause one has to verify in sophisticated experiments, that this approach is stable.
Typically, you can take a pre-trained model and retrain it on your new dataset by only changing the weights of the last layer(s).
Some loss functions even measures the difference between the high-level features of two images, typically extracted from a pre-trained CNN (Perceptual Loss).
[1]Matt Zeiler did an amazing work on these findings 10 years ago (https://arxiv.org/abs/1311.2901).