Feature Space Analysis by Guided Diffusion Model
The paper proposes a decoder that generates images specifically tailored to match a user-defined feature. This allows researchers to rigorously analyze how different deep neural networks extract features by measuring the distance between those extracted features, revealing insights into what attributes are encoded in the network's representation.