Teaching AI to See Transparent Objects | #TeamSeas

Why is it challenging for algorithms to detect transparent objects?

• They reflect and refract light differently.

• They are too small to be detected.

• They emit their own light.

• They are always in motion.

What is a common assumption made by many computer vision systems about objects?

• Objects are always opaque.

• Objects reflect light uniformly in all directions.

• Objects are always stationary.

• Objects emit sound.

What is the primary function of the Clear Grasp model?

• To create 3D maps of opaque objects.

• To enhance image resolution.

• To identify and grasp transparent objects accurately.

• To detect motion in video footage.

Why did researchers use synthetic data to train the Clear Grasp model?

• Synthetic data is more accurate.

• Real-world data is challenging and expensive to obtain.

• Synthetic data is easier to process.

• Real-world data is not available.

Apart from robotics, where else can the Clear Grasp model be useful?

• In enhancing video game graphics.

• In identifying plastic waste in water bodies.

• In developing virtual reality environments.

• In improving smartphone cameras.