3 papers
cs.CV2025
Patch-Level Kernel Alignment for Dense Self-Supervised Learning
Juan Yeo, Ijun Jang, Taesup Kim
Dense self-supervised learning (SSL) methods showed its effectiveness in enhancing the fine-grained semantic understandings of vision models. However, existing approaches often rel…
cs.CV2025
ATAS: Any-to-Any Self-Distillation for Enhanced Open-Vocabulary Dense Prediction
Juan Yeo, Soonwoo Cha, Jiwoo Song +2
Vision-language models such as CLIP have recently propelled open-vocabulary dense prediction tasks by enabling recognition of a broad range of visual concepts. However, CLIP still…
cs.SD2024
When Vision Models Meet Parameter Efficient Look-Aside Adapters Without Large-Scale Audio Pretraining
Juan Yeo, Jinkwan Jang, Kyubyung Chae +2
Recent studies show that pretrained vision models can boost performance in audio downstream tasks. To enhance the performance further, an additional pretraining stage with large sc…