5 papers
Prototype-Enhanced Confidence Modeling for Cross-Modal Medical Image-Report Retrieval
Shreyank N Gowda, Xiaobo Jin, Christian Wagner
In cross-modal retrieval tasks, such as image-to-report and report-to-image retrieval, accurately aligning medical images with relevant text reports is essential but challenging du…
Interpretable Zero-shot Learning with Infinite Class Concepts
Zihan Ye, Shreyank N Gowda, Shiming Chen +3
Zero-shot learning (ZSL) aims to recognize unseen classes by aligning images with intermediate class semantics, like human-annotated concepts or class definitions. An emerging alte…
Is Temporal Prompting All We Need For Limited Labeled Action Recognition?
Shreyank N Gowda, Boyan Gao, Xiao Gu +1
Video understanding has shown remarkable improvements in recent years, largely dependent on the availability of large scaled labeled datasets. Recent advancements in visual-languag…
ZeroDiff: Solidified Visual-Semantic Correlation in Zero-Shot Learning
Zihan Ye, Shreyank N. Gowda, Xiaowei Huang +4
Zero-shot Learning (ZSL) aims to enable classifiers to identify unseen classes. This is typically achieved by generating visual features for unseen classes based on learned visual-…
Improved Feature Generating Framework for Transductive Zero-shot Learning
Zihan Ye, Xinyuan Ru, Shiming Chen +3
Feature Generative Adversarial Networks have emerged as powerful generative models in producing high-quality representations of unseen classes within the scope of Zero-shot Learnin…