title: CCMNet: Leveraging Calibrated Color Correction Matrices for Cross-Camera
    Color Constancy
summary: Computational color constancy, or white balancing, is a key module in a
  camera's image signal processor (ISP) that corrects color casts from scene
  lighting. Because this operation occurs in the camera-specific raw color space,
  white balance algorithms must adapt to different cameras. This paper introduces
  a learning-based method for cross-camera color constancy that generalizes to
  new cameras without retraining. Our method leverages pre-calibrated color
  correction matrices (CCMs) available on ISPs that map the camera's raw color
  space to a standard space (e.g., CIE XYZ). Our method uses these CCMs to
  transform predefined illumination colors (i.e., along the Planckian locus) into
  the test camera's raw space. The mapped illuminants are encoded into a compact
  camera fingerprint embedding (CFE) that enables the network to adapt to unseen
  cameras. To prevent overfitting due to limited cameras and CCMs during
  training, we introduce a data augmentation technique that interpolates between
  cameras and their CCMs. Experimental results across multiple datasets and
  backbones show that our method achieves state-of-the-art cross-camera color
  constancy while remaining lightweight and relying only on data readily
  available in camera ISPs.
paper_authors._id: 6801eaa05246a16677d1f2d9
paper_authors.name: Dongyoung Kim
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-04-18T09:38:39.520Z
paper_authors._id: 645dcc0da19f3e64bbf36492
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/645dcc0da19f3e64bbf36492/SPGOweEnV5syFFpf40niQ.png
paper_authors.fullname: Dongyoung Kim
paper_authors.type: user
paper_authors.user: dongyong2
paper_authors._id: 6801eaa05246a16677d1f2da
paper_authors.name: Mahmoud Afifi
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-05-16T07:13:03.166Z
paper_authors._id: 6574973c05e573071548922c
paper_authors.avatarUrl: /avatars/9f7858e27ccc239fdee5dd6fab2685c6.svg
paper_authors.fullname: Mahmoud Afifi
paper_authors.type: user
paper_authors.user: mafifi
paper_authors._id: 6801eaa05246a16677d1f2db
paper_authors.name: Dongyun Kim
paper_authors._id: 6801eaa05246a16677d1f2dc
paper_authors.name: Michael S. Brown
paper_authors._id: 6801eaa05246a16677d1f2dd
paper_authors.name: Seon Joo Kim
paper_title: CCMNet: Leveraging Calibrated Color Correction Matrices for Cross-Camera
    Color Constancy
paper_summary: Computational color constancy, or white balancing, is a key module in a
  camera's image signal processor (ISP) that corrects color casts from scene
  lighting. Because this operation occurs in the camera-specific raw color space,
  white balance algorithms must adapt to different cameras. This paper introduces
  a learning-based method for cross-camera color constancy that generalizes to
  new cameras without retraining. Our method leverages pre-calibrated color
  correction matrices (CCMs) available on ISPs that map the camera's raw color
  space to a standard space (e.g., CIE XYZ). Our method uses these CCMs to
  transform predefined illumination colors (i.e., along the Planckian locus) into
  the test camera's raw space. The mapped illuminants are encoded into a compact
  camera fingerprint embedding (CFE) that enables the network to adapt to unseen
  cameras. To prevent overfitting due to limited cameras and CCMs during
  training, we introduce a data augmentation technique that interpolates between
  cameras and their CCMs. Experimental results across multiple datasets and
  backbones show that our method achieves state-of-the-art cross-camera color
  constancy while remaining lightweight and relying only on data readily
  available in camera ISPs.
paper_ai_summary: A learning-based method for cross-camera color constancy uses pre-calibrated color correction matrices to create a camera fingerprint embedding, achieving state-of-the-art performance with limited data and without retraining.
paper_ai_keywords: white balancing image signal processor ISP color casts raw color space cross-camera color constancy color correction matrices CCMs Planckian locus camera fingerprint embedding CFE data augmentation interpolation