ePoster · Computer Vision
Navigating through the Latent Spaces in Generative Models
Antoniya Boyanova, Tahmineh Koosha, Marco Rothermel, Hamidreza Jamalabadi · Bernstein Conference 2024
Understanding how visual attributes influence cognitive properties, such as memorability and emotional valence, is crucial for advancements in computational neuroscience and AI-driven image processing. Previous work has introduced a research framework that uses generative models to learn the complex nonlinear mapping between visual attributes and cognitive properties (Goetschalckx et al., 2019). This approach identifies transformations in the latent space of a generative model, which, when applied, generate images with tailored visual attributes that can enhance or diminish targeted cognitive