1 citations · 2 across the 5 of their papers we have counts for
5 papers
DailyMAE: Towards Pretraining Masked Autoencoders in One Day
Jiantao Wu, Shentong Mo, Sara Atito +3
Recently, masked image modeling (MIM), an important self-supervised learning (SSL) method, has drawn attention for its effectiveness in learning data representation from unlabeled…
Masked Momentum Contrastive Learning for Zero-shot Semantic Understanding
Jiantao Wu, Shentong Mo, Muhammad Awais +3
Self-supervised pretraining (SSP) has emerged as a popular technique in machine learning, enabling the extraction of meaningful feature representations without labelled data. In th…
Variantional autoencoder with decremental information bottleneck for disentanglement
Jiantao Wu, Shentong Mo, Xiang Yang +4
One major challenge of disentanglement learning with variational autoencoders is the trade-off between disentanglement and reconstruction fidelity. Previous studies, which increase…
DEFT: Distilling Entangled Factors by Preventing Information Diffusion
Jiantao Wu, Lin Wang, Bo Yang +3
Disentanglement is a highly desirable property of representation owing to its similarity to human understanding and reasoning. Many works achieve disentanglement upon information b…
Angular Learning: Toward Discriminative Embedded Features
JT Wu, L. Wang
The margin-based softmax loss functions greatly enhance intra-class compactness and perform well on the tasks of face recognition and object classification. Outperformance, however…