7 papers
From Events to Clarity: The Event-Guided Diffusion Framework for Dehazing
Ling Wang, Yunfan Lu, Wenzong Ma +3
Clear imaging under hazy conditions is a critical task. Prior-based and neural methods have improved results. However, they operate on RGB frames, which suffer from limited dynamic…
Beyond Boundaries: Leveraging Vision Foundation Models for Source-Free Object Detection
Huizai Yao, Sicheng Zhao, Pengteng Li +6
Source-Free Object Detection (SFOD) aims to adapt a source-pretrained object detector to a target domain without access to source data. However, existing SFOD methods predominantly…
You only need 4 extra tokens: Synergistic Test-time Adaptation for LLMs
Yijie Xu, Huizai Yao, Zhiyu Guo +5
Large language models (LLMs) are increasingly deployed in specialized domains such as finance, medicine, and agriculture, where they face significant distribution shifts from their…
See&Trek: Training-Free Spatial Prompting for Multimodal Large Language Model
Pengteng Li, Pinhao Song, Wuyang Li +5
We introduce SEE&TREK, the first training-free prompting framework tailored to enhance the spatial understanding of Multimodal Large Language Models (MLLMS) under vision-only const…
From Events to Enhancement: A Survey on Event-Based Imaging Technologies
Yunfan Lu, Xiaogang Xu, Pengteng Li +4
Event cameras offering high dynamic range and low latency have emerged as disruptive technologies in imaging. Despite growing research on leveraging these benefits for different im…
SEE: See Everything Every Time -- Adaptive Brightness Adjustment for Broad Light Range Images via Events
Yunfan Lu, Xiaogang Xu, Hao Lu +8
Event cameras, with a high dynamic range exceeding , significantly outperform traditional embedded cameras, robustly recording detailed changing information under various li…