Deep Learning

Contrastive Learning for Color Constancy accepted at CVPR 2021

CLCC

CLCC: Contrastive Learning for Color Constancy (CVPR 2021)
Yi-Chen Lo*, Chia-Che Chang*, Hsuan-Chao Chiu, Yu-Hao Huang, Chia-Ping Chen, Yu-Lin Chang, Kevin Jou

MediaTek Inc., Hsinchu, Taiwan

(*) indicates equal contribution.

We preprocess each fold of dataset and stored in .pkl format for each sample. Each sample contains:

  • Raw image: Mask color checker; Subtract black level; Convert to uint16 [0, 65535] BGR numpy array with shape (H, W, 3).
  • RGB label: L2-normalized numpy vector with shape (3,).
  • Color checker: [0, 4095] BGR numpy array with shape (24, 3) for raw-to-raw mapping presented in our paper (see util/raw2raw.py and also section 4.3 in our paper). A few of them are stored in all zeros due to the failure of color checker detection. Note that we convert it into

     

     

     

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