3 papers
cs.CV2026
Advancing All-Weather Building Damage Mapping to the Instance Level: Outcomes and Insights from the 2026 Bright Challenge
Hongruixuan Chen, He Huang, Haifeng Wang +19
Rapid post-disaster response requires timely, building-level information on whether structures remain intact, are damaged, or are destroyed. Post-event optical imagery, however, ma…
cs.CV2025
Measuring and Mitigating Hallucinations in Vision-Language Dataset Generation for Remote Sensing
Madeline Anderson, Miriam Cha, William T. Freeman +3
Vision language models have achieved impressive results across various fields. However, adoption in remote sensing remains limited, largely due to the scarcity of paired image-text…
cs.CV2025
Improving Medical Visual Representations via Radiology Report Generation
Keegan Quigley, Miriam Cha, Josh Barua +4
Vision-language pretraining has been shown to produce high-quality visual encoders which transfer efficiently to downstream computer vision tasks. Contrastive learning approaches h…