5 citations · 12 across the 7 of their papers we have counts for
4 papers · 1 filter
OracleGS: Grounding Generative Priors for Sparse-View Gaussian Splatting
Atakan Topaloglu, Kunyi Li, Michael Niemeyer +3
Sparse-view novel view synthesis is fundamentally ill-posed due to severe geometric ambiguity. Current methods are caught in a trade-off: regressive models are geometrically faithf…
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-Resolution
M. Akin Yilmaz, Ahmet Bilican, A. Murat Tekalp
Balancing reconstruction quality versus model efficiency remains a critical challenge in lightweight single image super-resolution (SISR). Despite the prevalence of attention mecha…
MMSR: Multiple-Model Learned Image Super-Resolution Benefiting From Class-Specific Image Priors
Cansu Korkmaz, A. Murat Tekalp, Zafer Dogan
Assuming a known degradation model, the performance of a learned image super-resolution (SR) model depends on how well the variety of image characteristics within the training set…
Perception-Distortion Trade-off in the SR Space Spanned by Flow Models
Cansu Korkmaz, A. Murat Tekalp, Zafer Dogan +2
Flow-based generative super-resolution (SR) models learn to produce a diverse set of feasible SR solutions, called the SR space. Diversity of SR solutions increases with the temper…