The Sound of Water: Inferring Physical Properties from Pouring Liquids

This dataset is associated with the paper "The Sound of Water: Inferring Physical Properties from Pouring Liquids".

TODO: add citation and paper details.

The dataset is stored in the following directory structure:

SoundOfWater/
|-- annotations
|-- assets
|-- audios
|-- README.md
|-- splits
|-- videos
`-- youtube_samples

6 directories, 1 file

The Sound of Water: Inferring Physical Properties from Pouring Liquids

Dataset Overview

Video and audio samples

The video and audio samples are stored in the ./videos/ and ./audios/ directories, respectively. Note that we have trimmed the videos between the precise start and end of the pouring action. If you need untrimmed videos, please contact us separately and we may be able to help.

The metadata for each video is a row in "./annotations/localisation.csv".

Splits

We create four splits of the dataset. All of the splits can be found in the ./splits/ directory. The splits are as follows:

Split	Opacity		Shapes			Containers	Videos	Description
	Transparent	Opaque	Cylinder	Semi-cone	Bottle
Train	✓	✗	✓	✓	✗	18	195	Transparent cylinder-like containers
Test I	✓	✗	✓	✓	✗	13	54	Test set with seen containers
Test II	✗	✓	✓	✓	✗	19	327	Test set with unseen containers
Test III	✓	✓	✓	✓	✓	25	434	Shape clf. with unseen containers

TODO: add test_III.txt file.

Annotations

The set of containers used is shown in this image:

Container measurements and other metadata

All metadata for the containers is stored in the ./annotations/ file.

File	Description
`localisation.csv`	Each row is metadata (e.g., container) for each video.
`containers.yaml`	Metadata for each container.
`liquids.yaml`	Metadata for each liquid.
`materials.yaml`	Metadata for each material.

Container bounding boxes

The bounding box annotations for containers are stored here: ./annotations/container_bboxes/. These are generated in a zero-shot manner using LangSAM.

YouTube samples

We also provide 4 samples searched from YouTube. These are used for qualitative evaluation.

Datasets:

bpiyush
/

sound-of-water