3 citations · 6 across the 19 of their papers we have counts for
8 papers · 1 filter
PortraitTalk: Towards Customizable One-Shot Audio-to-Talking Face Generation
Fatemeh Nazarieh, Zhenhua Feng, Diptesh Kanojia +2
Audio-driven talking face generation is a challenging task in digital communication. Despite significant progress in the area, most existing methods concentrate on audio-lip synchr…
Rethinking Positive Pairs in Contrastive Learning
Jiantao Wu, Sara Atito, Zhenhua Feng +3
The training methods in AI do involve semantically distinct pairs of samples. However, their role typically is to enhance the between class separability. The actual notion of simil…
Probabilistically Aligned View-unaligned Clustering with Adaptive Template Selection
Wenhua Dong, Xiao-Jun Wu, Zhenhua Feng +3
In most existing multi-view modeling scenarios, cross-view correspondence (CVC) between instances of the same target from different views, like paired image-text data, is a crucial…
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…
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…
DiCoM -- Diverse Concept Modeling towards Enhancing Generalizability in Chest X-Ray Studies
Abhijeet Parida, Daniel Capellan-Martin, Sara Atito +4
Chest X-Ray (CXR) is a widely used clinical imaging modality and has a pivotal role in the diagnosis and prognosis of various lung and heart related conditions. Conventional automa…