4 papers
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…
Stylized Structural Patterns for Improved Neural Network Pre-training
Farnood Salehi, Vandit Sharma, Amirhossein Askari Farsangi +1
Modern deep learning models in computer vision require large datasets of real images, which are difficult to curate and pose privacy and legal concerns, limiting their commercial u…