Riccardo De Matteo
Papers
2
Total Citations
40
H-Index
2
About
Riccardo De Matteo is an emerging researcher specializing in computer vision and neural rendering, with a particular focus on novel view synthesis and physically-based relighting of real-world objects. His most notable contribution is the development of the ReNe (Relighting NeRF) dataset, introduced in his 2023 work "ReLight My NeRF: A Dataset for Novel View Synthesis and Relighting of Real World Objects," which addresses the challenging problem of rendering scenes under previously unobserved lighting conditions using Neural Radiance Fields (NeRF). By capturing real-world objects under precise one-light-at-a-time (OLAT) conditions with accurate annotations, De Matteo and his collaborators provided the research community with a rigorous benchmark to advance relighting methodologies — a long-standing challenge in photorealistic 3D reconstruction. The work has garnered 37 citations, signaling meaningful early impact within the rapidly evolving neural rendering landscape. De Matteo's research sits at the intersection of inverse rendering, data-driven illumination modeling, and 3D scene understanding, making his contributions particularly relevant to researchers and practitioners working on augmented reality, visual effects, and immersive media applications.
Research Focus
Key Achievements
Top Papers
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- 2