9 papers
Off the Planckian Locus: Using 2D Chromaticity to Improve In-Camera Color
SaiKiran Tedla, Joshua E. Little, Hakki Can Karaimer +1
Traditional in-camera colorimetric mapping relies on correlated color temperature (CCT)-based interpolation between pre-calibrated transforms optimized for Planckian illuminants su…
Dark3R: Learning Structure from Motion in the Dark
Andrew Y Guo, Anagh Malik, SaiKiran Tedla +7
We introduce Dark3R, a framework for structure from motion in the dark that operates directly on raw images with signal-to-noise ratios (SNRs) below dB -- a regime where conve…
Learning to Refocus with Video Diffusion Models
SaiKiran Tedla, Zhoutong Zhang, Xuaner Zhang +1
Focus is a cornerstone of photography, yet autofocus systems often fail to capture the intended subject, and users frequently wish to adjust focus after capture. We introduce a nov…
Generating the Past, Present and Future from a Motion-Blurred Image
SaiKiran Tedla, Kelly Zhu, Trevor Canham +4
We seek to answer the question: what can a motion-blurred image reveal about a scene's past, present, and future? Although motion blur obscures image details and degrades visual qu…
Towards Imperceptible Watermarking Via Environment Illumination for Consumer Cameras
Hodaka Kawachi, Tomoya Nakamura, Hiroaki Santo +4
This paper introduces a method for using LED-based environmental lighting to produce visually imperceptible watermarks for consumer cameras. Our approach optimizes an LED light sou…
Improved Mapping Between Illuminations and Sensors for RAW Images
Abhijith Punnappurath, Luxi Zhao, Hoang Le +3
RAW images are unprocessed camera sensor output with sensor-specific RGB values based on the sensor's color filter spectral sensitivities. RAW images also incur strong color casts…