3 citations · 4 across the 8 of their papers we have counts for
6 papers · 1 filter
HiGS: History-Guided Sampling for Plug-and-Play Enhancement of Diffusion Models
Seyedmorteza Sadat, Farnood Salehi, Romann M. Weber
While diffusion models have made remarkable progress in image generation, their outputs can still appear unrealistic and lack fine details, especially when using fewer number of ne…
HiWave: Training-Free High-Resolution Image Generation via Wavelet-Based Diffusion Sampling
Tobias Vontobel, Seyedmorteza Sadat, Farnood Salehi +1
Diffusion models have emerged as the leading approach for image synthesis, demonstrating exceptional photorealism and diversity. However, training diffusion models at high resoluti…
Guidance in the Frequency Domain Enables High-Fidelity Sampling at Low CFG Scales
Seyedmorteza Sadat, Tobias Vontobel, Farnood Salehi +1
Classifier-free guidance (CFG) has become an essential component of modern conditional diffusion models. Although highly effective in practice, the underlying mechanisms by which C…
Token Perturbation Guidance for Diffusion Models
Javad Rajabi, Soroush Mehraban, Seyedmorteza Sadat +1
Classifier-free guidance (CFG) has become an essential component of modern diffusion models to enhance both generation quality and alignment with input conditions. However, CFG req…
Efficient Distillation of Classifier-Free Guidance using Adapters
Cristian Perez Jensen, Seyedmorteza Sadat
While classifier-free guidance (CFG) is essential for conditional diffusion models, it doubles the number of neural function evaluations (NFEs) per inference step. To mitigate this…
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…