12 papers · 1 filter
BurstGP: Enhancing Raw Burst Image Super Resolution with Generative Priors
Dong Huo, Tristan Aumentado-Armstrong, Samrudhdhi B. Rangrej +8
Burst image super resolution (BISR) aims to construct a single high-resolution (HR) image by aggregating information from multiple low-resolution (LR) frames, relying on temporal r…
Face2Scene: Using Facial Degradation as an Oracle for Diffusion-Based Scene Restoration
Amirhossein Kazerouni, Maitreya Suin, Tristan Aumentado-Armstrong +6
Recent advances in image restoration have enabled high-fidelity recovery of faces from degraded inputs using reference-based face restoration models (Ref-FR). However, such methods…
RawGen: Learning Camera Raw Image Generation
Dongyoung Kim, Junyong Lee, Abhijith Punnappurath +4
Cameras capture scene-referred linear raw images, which are processed by onboard image signal processors (ISPs) into display-referred 8-bit sRGB outputs. Although raw data is more…
RAW-Domain Degradation Models for Realistic Smartphone Super-Resolution
Ali Mosleh, Faraz Ali, Fengjia Zhang +4
Digital zoom on smartphones relies on learning-based super-resolution (SR) models that operate on RAW sensor images, but obtaining sensor-specific training data is challenging due…
Towards High-Fidelity Gaussian Splatting with Queried-Convolution Neural Networks
Abhinav Kumar, Tristan Aumentado-Armstrong, Lazar Valkov +4
Gaussian Splatting has revolutionized the field of Novel View Synthesis (NVS) with faster training and real-time rendering. However, its reconstruction fidelity still trails behind…
Hallucination Score: Towards Mitigating Hallucinations in Generative Image Super-Resolution
Weiming Ren, Raghav Goyal, Zhiming Hu +3
Generative super-resolution (GSR) currently sets the state-of-the-art in terms of perceptual image quality, overcoming the "regression-to-the-mean" blur of prior non-generative mod…