5 citations · 5 across the 11 of their papers we have counts for
10 papers · 1 filter
Neuromorphic Object Detection: An In-Depth Study and Future Directions
Jianing Li, Dianze Li, Arren Glover +5
Conventional frame-based cameras face significant challenges in detecting objects under high-speed motion blur or in low-light environments. Neuromorphic cameras provide asynchrono…
EventFlash: Towards Efficient MLLMs for Event-Based Vision
Shaoyu Liu, Jianing Li, Guanghui Zhao +4
Event-based multimodal large language models (MLLMs) enable robust perception in high-speed and low-light scenarios, addressing key limitations of frame-based MLLMs. However, curre…
Learning to Remove Lens Flare in Event Camera
Haiqian Han, Lingdong Kong, Jianing Li +7
Event cameras have the potential to revolutionize vision systems with their high temporal resolution and dynamic range, yet they remain susceptible to lens flare, a fundamental opt…
EventBench: Towards Comprehensive Benchmarking of Event-based MLLMs
Shaoyu Liu, Jianing Li, Guanghui Zhao +2
Multimodal large language models (MLLMs) have made significant advancements in event-based vision, yet the comprehensive evaluation of their capabilities within a unified benchmark…
Towards Understanding How Knowledge Evolves in Large Vision-Language Models
Sudong Wang, Yunjian Zhang, Yao Zhu +4
Large Vision-Language Models (LVLMs) are gradually becoming the foundation for many artificial intelligence applications. However, understanding their internal working mechanisms h…
EventGPT: Event Stream Understanding with Multimodal Large Language Models
Shaoyu Liu, Jianing Li, Guanghui Zhao +5
Event cameras record visual information as asynchronous pixel change streams, excelling at scene perception under unsatisfactory lighting or high-dynamic conditions. Existing multi…