7 papers
Understand Before Detect: Vision--Language Learning for Omni-Domain Infrared Small Target Detection
Haoyang Yuan, Boyang Li, Yingqian Wang +7
Omni-domain infrared small target (IRST) detection is crucial for infrared surveillance, yet remains challenging due to heterogeneous imaging domains and inconsistent target charac…
Toward Accountable AI-Generated Content on Social Platforms: Steganographic Attribution and Multimodal Harm Detection
Xinlei Guan, David Arosemena, Tejaswi Dhandu +7
The rapid growth of generative AI has introduced new challenges in content moderation and digital forensics. In particular, benign AI-generated images can be paired with harmful or…
Taxonomy and Consistency Analysis of Safety Benchmarks for AI Agents
Miles Q. Li, Benjamin C. M. Fung, Boyang Li +2
The rapid deployment of LLM-based autonomous agents has introduced safety risks that extend far beyond traditional LLM concerns, prompting a proliferation of safety benchmarks sinc…
Focus on What Really Matters in Low-Altitude Governance: A Management-Centric Multi-Modal Benchmark with Implicitly Coordinated Vision-Language Reasoning Framework
Hao Chang, Zhihui Wang, Lingxiang Wu +5
Low-altitude vision systems are becoming a critical infrastructure for smart city governance. However, existing object-centric perception paradigms and loosely coupled vision-langu…
Rethinking IRSTD: Single-Point Supervision Guided Encoder-only Framework is Enough for Infrared Small Target Detection
Rixiang Ni, Boyang Li, Jun Chen +6
Infrared small target detection (IRSTD) aims to separate small targets from clutter backgrounds. Extensive research is dedicated to the pixel-level supervision-guided "encoder-deco…
RRCANet: Recurrent Reusable-Convolution Attention Network for Infrared Small Target Detection
Yongxian Liu, Boyang Li, Ting Liu +2
Infrared small target detection is a challenging task due to its unique characteristics (e.g., small, dim, shapeless and changeable). Recently published CNN-based methods have achi…