Weakly Supervised Action Segmentation (Transcript)

The Breakfast Actions Dataset comprises of 10 actions related to breakfast preparation, performed by 52 different individuals in 18 different kitchens. The dataset is one of the largest fully annotated datasets available. The actions are recorded “in the wild” as opposed to a single controlled lab environment. It consists of over 77 hours of video recordings. Source: https://serre-lab.clps.brown.edu/resource/breakfast-actions-dataset/ Image Source: https://serre-lab.clps.brown.edu/resource/breakfast-actions-dataset/

EgoProceL is a large-scale dataset for procedure learning. It consists of 62 hours of egocentric videos recorded by 130 subjects performing 16 tasks for procedure learning. EgoProceL contains videos and key-step annotations for multiple tasks from CMU-MMAC, EGTEA Gaze+, and individual tasks like toy-bike assembly, tent assembly, PC assembly, and PC disassembly. EgoProceL overcomes the limitations of third-person videos. As, using third-person videos makes the manipulated object small in appearance and often occluded by the actor, leading to significant errors. In contrast, we observe that videos obtained from first-person (egocentric) wearable cameras provide an unobstructed and clear view of the action.