2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CV2023
Augment the Pairs: Semantics-Preserving Image-Caption Pair Augmentation for Grounding-Based Vision and Language Models
Jingru Yi, Burak Uzkent, Oana Ignat +4
Grounding-based vision and language models have been successfully applied to low-level vision tasks, aiming to precisely locate objects referred in captions. The effectiveness of g…
cs.AI2023★ 2 cited
GOHSP: A Unified Framework of Graph and Optimization-based Heterogeneous Structured Pruning for Vision Transformer
Miao Yin, Burak Uzkent, Yilin Shen +2
The recently proposed Vision transformers (ViTs) have shown very impressive empirical performance in various computer vision tasks, and they are viewed as an important type of foun…