Marco Toschi
Papers
2
Total Citations
40
H-Index
2
About
Marco Toschi is a computer vision researcher whose work sits at the cutting edge of neural rendering, novel view synthesis, and image-based relighting. He is best known for his contributions to Neural Radiance Fields (NeRF), particularly in extending their capabilities beyond static lighting conditions to handle dynamic, unobserved illumination scenarios — a notoriously challenging problem in photorealistic rendering. His most prominent contribution is the introduction of **ReNe (Relighting NeRF)**, a carefully curated dataset of real-world objects captured under one-light-at-a-time (OLAT) conditions with precise annotations, designed to benchmark and advance methods for simultaneous novel view synthesis and relighting. This work has garnered 40 citations across its publications, reflecting its value to the research community as both a methodological framework and a practical resource. By addressing the gap between idealized synthetic environments and the complexities of real-world lighting, Toschi's research provides foundational tools for applications in augmented reality, visual effects, and digital content creation. His work exemplifies the growing intersection of data-driven approaches and physically grounded rendering, making him a noteworthy contributor to the modern neural rendering landscape.
Research Focus
Key Achievements
Top Papers
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- 2