6 papers
Your Pre-trained Diffusion Model Secretly Knows Restoration
Sudarshan Rajagopalan, Vishal M. Patel
Pre-trained diffusion models have enabled significant advancements in All-in-One Restoration (AiOR), offering improved perceptual quality and generalization. However, diffusion-bas…
RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restoration
Sudarshan Rajagopalan, Kartik Narayan, Vishal M. Patel
The use of latent diffusion models (LDMs) such as Stable Diffusion has significantly improved the perceptual quality of All-in-One image Restoration (AiOR) methods, while also enha…
SINR: Sparsity Driven Compressed Implicit Neural Representations
Dhananjaya Jayasundara, Sudarshan Rajagopalan, Yasiru Ranasinghe +2
Implicit Neural Representations (INRs) are increasingly recognized as a versatile data modality for representing discretized signals, offering benefits such as infinite query resol…
GenDeg: Diffusion-based Degradation Synthesis for Generalizable All-In-One Image Restoration
Sudarshan Rajagopalan, Nithin Gopalakrishnan Nair, Jay N. Paranjape +1
Deep learning-based models for All-In-One Image Restoration (AIOR) have achieved significant advancements in recent years. However, their practical applicability is limited by poor…
AWRaCLe: All-Weather Image Restoration using Visual In-Context Learning
Sudarshan Rajagopalan, Vishal M. Patel
All-Weather Image Restoration (AWIR) under adverse weather conditions is a challenging task due to the presence of different types of degradations. Prior research in this domain re…
Low-rank Adaptation-based All-Weather Removal for Autonomous Navigation
Sudarshan Rajagopalan, Vishal M. Patel
All-weather image restoration (AWIR) is crucial for reliable autonomous navigation under adverse weather conditions. AWIR models are trained to address a specific set of weather co…