OSDD (Object State Detection Dataset)

The Objects States Detection Dataset consists of images depicting everyday household objects in a number of different states. The ground-truth annotations involve the labels and bounding boxes spanning 18 object categories and 9 state classes. The object categories are: \textit{bottle, jar, tub, book, drawer, door, cup, mug, glass, bowl, basket, box, phone, charger, socket, towel, shirt} and \textit{newspaper}. The 9 state classes are: \textit{open, close, empty, containing something liquid (CL), containing something solid (CS), plugged, unplugged, folded} and \textit{unfolded}.

The images were obtained by selecting video frames from the something-something V2 Dataset~\url{https://developer.qualcomm.com/software/ai-datasets/something-something}. Specifically, images containing visually salient objects and states of the aforementioned categories were captured and annotated with bounding-boxes and ground truth labels referring to the corresponding object categories and state classes. Overall, the dataset contains 13,744 images and 19,018 annotations obtained by selecting the first, last and middle frames of 9,015 videos, after checking that each of them contains salient information.