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We are curating this publication list to reflect CVAIL's most representative work in this area. Check back soon for a focused selection of papers, project links, and visual summaries.
Natural Language Processing
Natural Language Processing at CVAIL combines learning-based perception with physically informed reasoning so models can operate under real-world constraints instead of idealized settings. We investigate multimodal learning, semantic grounding, and language-aware perception systems that link textual structure with visual evidence.
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Thermal Imaging
Learning robust scene understanding when visible light is unreliable, low contrast, or absent.
Dense Prediction
Estimating structure at the pixel level to recover geometry, semantics, and uncertainty from complex scenes.
NLOS Imaging
Recovering hidden geometry and activity from indirect light transport beyond the line of sight.
Remote Sensing
Analyzing large-scale aerial and satellite imagery to monitor land, infrastructure, and environmental change.
Rendering
Modeling how light interacts with geometry and materials to synthesize or recover realistic visual structure.