10 papers
Regressor-Guided Image Editing Shifts Emotion and Disengagement Timing in Social Media
Christoph Gebhardt, Robin Willardt, Seyedmorteza Sadat +5
Internet overuse is a widespread phenomenon in today's digital society. Existing interventions, such as time limits or grayscaling, often rely on restrictive controls that provoke…
Eliminating Oversaturation and Artifacts of High Guidance Scales in Diffusion Models
Seyedmorteza Sadat, Otmar Hilliges, Romann M. Weber
Classifier-free guidance (CFG) is crucial for improving both generation quality and alignment between the input condition and final output in diffusion models. While a high guidanc…
No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models
Seyedmorteza Sadat, Manuel Kansy, Otmar Hilliges +1
Classifier-free guidance (CFG) has become the standard method for enhancing the quality of conditional diffusion models. However, employing CFG requires either training an uncondit…
RILe: Reinforced Imitation Learning
Mert Albaba, Sammy Christen, Thomas Langarek +3
Acquiring complex behaviors is essential for artificially intelligent agents, yet learning these behaviors in high-dimensional settings poses a significant challenge due to the vas…
Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction
M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel +5
Understanding drivers' decision-making is crucial for road safety. Although predicting the ego-vehicle's path is valuable for driver-assistance systems, existing methods mainly foc…
LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models
Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley +2
Advances in latent diffusion models (LDMs) have revolutionized high-resolution image generation, but the design space of the autoencoder that is central to these systems remains un…