Mixed Mutual Transfer for Long-Tailed Image Classification
Ning Ren,
Xiaosong Li,
Yanxia Wu
et al.
Abstract:Real-world datasets often follow a long-tailed distribution, where a few majority (head) classes contain a large number of samples, while many minority (tail) classes contain significantly fewer samples. This imbalance creates an information disparity between head and tail classes, which can negatively impact the performance of deep networks. Some transfer knowledge techniques attempt to mitigate this gap by generating additional minority samples, either through oversampling the tail classes or transferring kn… Show more
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