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Found 7 papers, 3 papers with code
AREA: Adaptive Reweighting via Effective Area for Long-Tailed Classification
Consequently, we estimate the size of the spanned space for each category, namely effective area, by detailedly analyzing its samples' distribution.
Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification
Since the covariance matrix of each category represents the feature transformation directions, we can sample new directions from similar categories to generate definitely different instances.
Ranked #50 on
Long-tail Learning
on CIFAR-10-LT (ρ=10)
MMF: Multi-Task Multi-Structure Fusion for Hierarchical Image Classification
Hierarchical classification is significant for complex tasks by providing multi-granular predictions and encouraging better mistakes.
Rescuing Deep Hashing from Dead Bits Problem
The proposed gradient amplifier and error-aware quantization loss are compatible with a variety of deep hashing methods.
Exploring Relations in Untrimmed Videos for Self-Supervised Learning
Then a designed sampling strategy is used to model relations for video clips.
Expert Training: Task Hardness Aware Meta-Learning for Few-Shot Classification
Some works in the optimization of deep neural networks have shown that a better arrangement of training data can make the classifier converge faster and perform better.
SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition
Scene text recognition is a hot research topic in computer vision.
