7 citations · 8 across the 8 of their papers we have counts for
9 papers
General Incomplete Multimodal Learning via Dynamic Quality Perception
Xiangyu Meng, Shicai Wei
Multimodal learning robust to missing modalities is essential for real-world applications. Existing methods mainly focus on inter-modality missing, where entire modalities are abse…
PDMP: Rethinking Balanced Multimodal Learning via Performance-Dominant Modality Prioritization
Shicai Wei, Chunbo Luo, Qiang Zhu +1
Multimodal learning has attracted increasing attention due to its practicality. However, it often suffers from insufficient optimization, where the multimodal model underperforms e…
Unbiased Dynamic Multimodal Fusion
Shicai Wei, Kaijie Zhang, Luyi Chen +2
Traditional multimodal methods often assume static modality quality, which limits their adaptability in dynamic real-world scenarios. Thus, dynamical multimodal methods are propose…
Improving Multimodal Learning via Imbalanced Learning
Shicai Wei, Chunbo Luo, Yang Luo
Multimodal learning often encounters the under-optimized problem and may perform worse than unimodal learning. Existing approaches attribute this issue to imbalanced learning acros…
Boosting Multimodal Learning via Disentangled Gradient Learning
Shicai Wei, Chunbo Luo, Yang Luo
Multimodal learning often encounters the under-optimized problem and may have worse performance than unimodal learning. Existing methods attribute this problem to the imbalanced le…
Robust Multimodal Learning via Representation Decoupling
Shicai Wei, Yang Luo, Yuji Wang +1
Multimodal learning robust to missing modality has attracted increasing attention due to its practicality. Existing methods tend to address it by learning a common subspace represe…
Scale Decoupled Distillation
Shicai Wei Chunbo Luo Yang Luo
Logit knowledge distillation attracts increasing attention due to its practicality in recent studies. However, it often suffers inferior performance compared to the feature knowled…
One-stage Modality Distillation for Incomplete Multimodal Learning
Shicai Wei, Yang Luo, Chunbo Luo
Learning based on multimodal data has attracted increasing interest recently. While a variety of sensory modalities can be collected for training, not all of them are always availa…
MMANet: Margin-aware Distillation and Modality-aware Regularization for Incomplete Multimodal Learning
Shicai Wei, Yang Luo, Chunbo Luo
Multimodal learning has shown great potentials in numerous scenes and attracts increasing interest recently. However, it often encounters the problem of missing modality data and t…