A weighted linear combination of SCL, RSG, and LDAM losses is shown to improve tail-class accuracy while largely preserving head-class accuracy on several long-tailed benchmarks.
Long-tailed recognition via weight balancing
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Solving the long-tailed distribution problem by exploiting the synergies and balance of different techniques
A weighted linear combination of SCL, RSG, and LDAM losses is shown to improve tail-class accuracy while largely preserving head-class accuracy on several long-tailed benchmarks.