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Sato Lab
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The lab reads the shape and texture of objects by capturing how light reflects and scatters.
AboutAbout the lab
Understanding scenes with physics-based models
Sato Lab studies computer vision, in which computers understand the world around them from images.
The lab proposes new physics-based models and develops algorithms that support scene understanding.
The lab works on 3D analysis, reflectance analysis, hyperspectral imaging, computational photography, and generative AI.
The lab is located at the National Institute of Informatics, and students in the Department of Computer Science at the University of Tokyo can be assigned to the lab and take part in its research.
Key terms
- Hyperspectral imaging
- A method of capturing images by separating light into fine wavelength bands. It reveals differences in materials that are hard to distinguish with the human eye.
- Event camera
- A camera that, instead of capturing the whole frame at fixed intervals, quickly records only the points where brightness changes.
- Polarization
- Light whose waves oscillate in an aligned direction. It provides clues to the orientation and material of the surface that reflected it.
ResearchResearch themes
The lab studies computer vision that uses physics-based models to understand scenes from images. Using polarization, hyperspectral imaging, event cameras, and other tools, it analyzes how light reflects and scatters, and proposes methods for capturing the shape and material of objects.
*Illustrative imageSeparating light to recover 3D shape with an event camera
Using only an event camera, the lab proposes a method that separates direct reflection from an object's surface from light that has been reflected and scattered in the surroundings, while also estimating rough depth.
*Illustrative imagePolarization imaging robust to noise and blur
Polarization images tend to be noisy with short exposures and blurred with long exposures. The lab proposes a framework that combines both kinds of images to recover clean, sharp polarization images.
*Illustrative imageReading the "texture" of paintings through light
To investigate the texture of the "milky white skin" in the works of the painter Léonard Foujita (Tsuguharu Fujita), the lab used a hyperspectral camera to analyze the fluorescence of white paint under ultraviolet light. It revealed that similar white paints had been applied differently according to their fluorescence properties.
*Illustrative imageRemoving flicker from event cameras
Flicker from fluorescent lights and LEDs introduces heavy noise into event camera recordings. The lab proposes a network that removes this flicker by using correlations in time and space.
MembersFaculty
The members of Sato Lab consist of faculty, researchers, research assistants, doctoral and master's students, and secretaries.As of 2026
- ProfessorImari Sato
- Assistant ProfessorYuta Asano
- Project Assistant ProfessorMihoko Shimano
- Project Assistant ProfessorChu Zhou
- Project Assistant ProfessorJinxiu Liang
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Photoelasticity - Spiked castor cup” Colin / CC BY-SA 4.0 (cropped)
- Separating light to recover 3D shape with an event camera: “Event camera comparison” TimoStoffregen / CC BY-SA 4.0 (cropped)
- Polarization imaging robust to noise and blur: “Photoelasticity - Clear CD case centre” Colin / CC BY-SA 4.0 (cropped)
- Reading the "texture" of paintings through light: “Different fluorescent minerals” Albarubescens / CC BY 4.0 (cropped)
- Removing flicker from event cameras: “Fluorescent light strip 2 tube” Chetvorno / CC0 (cropped)
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