28 citations · 29 across the 10 of their papers we have counts for
12 papers
PrismGPT: Proxy-Guided Learning for Region-Aware Photo Editing with Self-Synthesized Reasoning
Ke Zhao, Hue Nguyen, Abhijith Punnappurath +3
Professional photo finishing relies on both global adjustments and region-specific local edits guided by semantic masks, yet current automated methods handle this workflow only par…
Adaptive Color Grading
Trevor D. Canham, Abhijith Punnappurath, Michael S. Brown
Independent control of tonescale regions (e.g., shadows, highlights) is essential for painters, photographers and cinematographers to bring 2D images to life. In image manipulation…
Addressing Image Authenticity When Cameras Use Generative AI
Umar Masud, Abhijith Punnappurath, Luxi Zhao +2
The ability of generative AI (GenAI) methods to photorealistically alter camera images has raised awareness about the authenticity of images shared online. Interestingly, images ca…
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…
Edit-aware RAW Reconstruction
Abhijith Punnappurath, Luxi Zhao, Ke Zhao +3
Users frequently edit camera images post-capture to achieve their preferred photofinishing style. While editing in the RAW domain provides greater accuracy and flexibility, most ed…
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…
Examining Joint Demosaicing and Denoising for Single-, Quad-, and Nona-Bayer Patterns
SaiKiran Tedla, Abhijith Punnappurath, Luxi Zhao +1
Camera sensors have color filters arranged in a mosaic layout, traditionally following the Bayer pattern. Demosaicing is a critical step camera hardware applies to obtain a full-ch…
Time-Aware Auto White Balance in Mobile Photography
Mahmoud Afifi, Luxi Zhao, Abhijith Punnappurath +3
Cameras rely on auto white balance (AWB) to correct undesirable color casts caused by scene illumination and the camera's spectral sensitivity. This is typically achieved using an…
Day-to-Night Image Synthesis for Training Nighttime Neural ISPs
Abhijith Punnappurath, Abdullah Abuolaim, Abdelrahman Abdelhamed +2
Many flagship smartphone cameras now use a dedicated neural image signal processor (ISP) to render noisy raw sensor images to the final processed output. Training nightmode ISP net…
Learning sRGB-to-Raw-RGB De-rendering with Content-Aware Metadata
Seonghyeon Nam, Abhijith Punnappurath, Marcus A. Brubaker +1
Most camera images are rendered and saved in the standard RGB (sRGB) format by the camera's hardware. Due to the in-camera photo-finishing routines, nonlinear sRGB images are undes…
CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks
Mahmoud Afifi, Abdelrahman Abdelhamed, Abdullah Abuolaim +2
Cameras currently allow access to two image states: (i) a minimally processed linear raw-RGB image state (i.e., raw sensor data) or (ii) a highly-processed nonlinear image state (e…
A Little Bit More: Bitplane-Wise Bit-Depth Recovery
Abhijith Punnappurath, Michael S. Brown
Imaging sensors digitize incoming scene light at a dynamic range of 10--12 bits (i.e., 1024--4096 tonal values). The sensor image is then processed onboard the camera and finally q…