23 citations · 23 across the 2 of their papers we have counts for
3 papers
E-MLNet: Enhanced Mutual Learning for Universal Domain Adaptation with Sample-Specific Weighting
Samuel Felipe dos Santos, Tiago Agostinho de Almeida, Jurandy Almeida
Universal Domain Adaptation (UniDA) seeks to transfer knowledge from a labeled source to an unlabeled target domain without assuming any relationship between their label sets, requ…
Budget-Aware Pruning: Handling Multiple Domains with Less Parameters
Samuel Felipe dos Santos, Rodrigo Berriel, Thiago Oliveira-Santos +2
Deep learning has achieved state-of-the-art performance on several computer vision tasks and domains. Nevertheless, it still has a high computational cost and demands a significant…
Faster and Accurate Compressed Video Action Recognition Straight from the Frequency Domain
Samuel Felipe dos Santos, Jurandy Almeida
Human action recognition has become one of the most active field of research in computer vision due to its wide range of applications, like surveillance, medical, industrial enviro…