After KAUST Academy
Deem graduated in computer science from Qassim University in 2026 with First Honors. At KAUST Academy, Deem explored whether AI can understand lighting from a single image, a question that began in the graduation project.
Summer project
Artificial Intelligence Specialization · Cohort 2026
Luma: Self-Supervised Realistic Lighting Estimation from Real Indoor Images
Estimating realistic indoor lighting from a single photograph remains challenging, because lighting is entangled with material and geometry. Previous methods still do not convey how the consistency and reflection of light is in real life or is computationally expensive. Luma aims to bridge the gap in existing light estimation methods by introducing a physics-grounded model trained with a physically-based differentiable renderer, to produce realistic lighting estimates from real indoor images.
With KAUST Academy
- Cohort 2026
Artificial Intelligence Specialization
King Khalid University · Artificial Intelligence Summer School
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