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Humans have rich understanding of liquid containers and their contents; forexample, we can effortlessly pour water from a pitcher to a cup. Doing sorequires estimating the volume of the cup, approximating the amount of water inthe pitcher, and predicting the behavior of water when we tilt the pitcher.Very little attention in computer vision has been made to liquids and theircontainers. In this paper, we study liquid containers and their contents, andpropose methods to estimate the volume of containers, approximate the amount ofliquid in them, and perform comparative volume estimations all from a singleRGB image. Furthermore, we show the results of the proposed model forpredicting the behavior of liquids inside containers when one tilts thecontainers. We also introduce a new dataset of Containers Of liQuid contEnt(COQE) that contains more than 5,000 images of 10,000 liquid containers incontext labelled with volume, amount of content, bounding box annotation, andcorresponding similar 3D CAD models.

See the Glass Half Full: Reasoning about Liquid Containers, their Volume and Content