Long Tail Learning On Cifar 100 Lt R 10

Error Rate

评测结果

各个模型在此基准测试上的表现结果

比较表格

模型名称	Error Rate
towards-calibrated-model-for-long-tailed	38.75
improving-calibration-for-long-tailed-1	36.8
supervised-contrastive-learning-on-blended	37.5
distributional-robustness-loss-for-long-tail	36.59
lpt-long-tailed-prompt-tuning-for-image	9
test-agnostic-long-tailed-recognition-by-test	36.4
a-simple-episodic-linear-probe-improves	40.9
class-wise-difficulty-balanced-loss-for	41.26
learning-imbalanced-datasets-with-label	41.29
global-and-local-mixture-consistency-1	26.53
visual-prompt-tuning	10.4
sure-survey-recipes-for-building-reliable-and	26.76
learning-prototype-classifiers-for-long	30.88
posterior-re-calibration-for-imbalanced	41.4
metasaug-meta-semantic-augmentation-for-long	38.72
long-tailed-classification-with-gradual	35.5
feature-generation-for-long-tail	38.87
long-tailed-recognition-by-mutual-information	33.0
difficulty-net-learning-to-predict-difficulty	34.78
a-unified-generalization-analysis-of-re	34.41
global-and-local-mixture-consistency-1	25.72
rethinking-the-value-of-labels-for-improving	41.09
cuda-curriculum-of-data-augmentation-for-long	35.4
parameter-efficient-long-tailed-recognition	8.7
long-tailed-recognition-by-learning-from-1	35.8
long-tail-learning-with-attributes	41.23
parameter-efficient-long-tailed-recognition	15.1
long-tailed-recognition-via-weight-balancing	31.33
disentangling-label-distribution-for-long	38.3
curvature-balanced-feature-manifold-learning	38.60
contrastive-learning-based-hybrid-networks	37.63