GenView is presented, a controllable framework that augments the diversity of positive views leveraging the power of pretrained generative models while preserving semantics, and an adaptive view generation method that dynamically adjusts the noise level in sampling to ensure the preservation of essential semantic meaning while introducing variability.
A lightweight learnable augmentation framework based on Extreme Learning Machines for self-supervised visual representation learning that improves linear evaluation performance relative to reproduced baselines across most settings and demonstrates that lightweight learnable augmentation can effectively enhance self-sup...
PAPT++ is introduced, a risk-aware adversarial generation-training framework for SDG that progressively exposes the classifier to challenging yet semantically consistent variations.
Zhi-Peng Xu, De Cheng, Xinyang Jiang et al.· 0 citations
Self-supervised representation-guided generative dataset distillation (SRG) is proposed, a framework that translates the SSL geometry into diffusion guidance and consistently outperforms the evaluated generative baselines across multiple datasets and IPC settings.
Mingzhuo Li, Guang Li, Linfeng Ye et al.· 0 citations
Extensive experiments on three ZSL benchmarks demonstrate that ZeroDiff++ not only achieves significant improvements over existing ZSL methods but also maintains robust performance even with scarce training data, and mitigates data scarcity further.
Zihan Ye, S. N. Gowda, Kai-Le Du et al.· IEEE Transactions on Pattern...· 0 citations
This work proposes a novel Historical Collaborative Learning (HCL) framework empowered by adaptive dual-state historical supervision that jointly exploits long-term and short-term historical knowledge to produce complementary supervision signals.
Xiaohong Zhang, Jianwen Xiang· Pattern Analysis and Applica...· 0 citations
A progressive multi-objective optimization framework is proposed that enhances t-SNE by integrating complementary loss functions, including a ranking-aware divergence (KLmax) and a Wasserstein-based term for global alignment.
S. Belhaouari, Skander Bensegueni, Lyes Fennour et al.· International Conference on...· 0 citations
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