1 citations · 1 across the 7 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.CV2024★ 1 cited
From Prototypes to General Distributions: An Efficient Curriculum for Masked Image Modeling
Jinhong Lin, Cheng-En Wu, Huanran Li +3
Masked Image Modeling (MIM) has emerged as a powerful self-supervised learning paradigm for visual representation learning, enabling models to acquire rich visual representations b…
cs.CV2024
Accelerating Augmentation Invariance Pretraining
Jinhong Lin, Cheng-En Wu, Yibing Wei +1
Our work tackles the computational challenges of contrastive learning methods, particularly for the pretraining of Vision Transformers (ViTs). Despite the effectiveness of contrast…
cs.CV2024
Patch Ranking: Efficient CLIP by Learning to Rank Local Patches
Cheng-En Wu, Jinhong Lin, Yu Hen Hu +1
Contrastive image-text pre-trained models such as CLIP have shown remarkable adaptability to downstream tasks. However, they face challenges due to the high computational requireme…