CAT (Context Adjustment Training)
Introduced by Kong et al. in Free Lunch for Co-Saliency Detection: Context Adjustment
CAT is a specialized dataset for co-saliency detection - one of the core tasks in the field of computer vision. This dataset is intended for both helping to assess the performance of vision algorithms and supporting research that aims to exploit large volumes of annotated data, e.g., for training deep neural networks. CAT consists of 33,500 images
Papers
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