3 papers
cs.CV2025
3D Semantic Segmentation for Post-Disaster Assessment
Nhut Le, Maryam Rahnemoonfar
The increasing frequency of natural disasters poses severe threats to human lives and leads to substantial economic losses. While 3D semantic segmentation is crucial for post-disas…
cs.CV2025
Think First, Assign Next (ThiFAN-VQA): A Two-stage Chain-of-Thought Framework for Post-Disaster Damage Assessment
Ehsan Karimi, Nhut Le, Maryam Rahnemoonfar
Timely and accurate assessment of damages following natural disasters is essential for effective emergency response and recovery. Recent AI-based frameworks have been developed to…
cs.CV2025
3DAeroRelief: The first 3D Benchmark UAV Dataset for Post-Disaster Assessment
Nhut Le, Ehsan Karimi, Maryam Rahnemoonfar
Timely assessment of structural damage is critical for disaster response and recovery. However, most prior work in natural disaster analysis relies on 2D imagery, which lacks depth…