480 citations · 490 across the 8 of their papers we have counts for
12 papers
MMDRFuse: Distilled Mini-Model with Dynamic Refresh for Multi-Modality Image Fusion
Yanglin Deng, Tianyang Xu, Chunyang Cheng +2
In recent years, Multi-Modality Image Fusion (MMIF) has been applied to many fields, which has attracted many scholars to endeavour to improve the fusion performance. However, the…
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action Recognition
Rongchang Li, Zhenhua Feng, Tianyang Xu +5
Compositional actions consist of dynamic (verbs) and static (objects) concepts. Humans can easily recognize unseen compositions using the learned concepts. For machines, solving su…
Investigating Self-Supervised Methods for Label-Efficient Learning
Srinivasa Rao Nandam, Sara Atito, Zhenhua Feng +2
Vision transformers combined with self-supervised learning have enabled the development of models which scale across large datasets for several downstream tasks like classification…
Pseudo Labelling for Enhanced Masked Autoencoders
Srinivasa Rao Nandam, Sara Atito, Zhenhua Feng +2
Masked Image Modeling (MIM)-based models, such as SdAE, CAE, GreenMIM, and MixAE, have explored different strategies to enhance the performance of Masked Autoencoders (MAE) by modi…
An Improved Graph Pooling Network for Skeleton-Based Action Recognition
Cong Wu, Xiao-Jun Wu, Tianyang Xu +1
Pooling is a crucial operation in computer vision, yet the unique structure of skeletons hinders the application of existing pooling strategies to skeleton graph modelling. In this…
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…