Oops! Predicting Unintentional Action in Video [article]

Dave Epstein, Boyuan Chen, Carl Vondrick
2019 arXiv   pre-print
From just a short glance at a video, we can often tell whether a person's action is intentional or not. Can we train a model to recognize this? We introduce a dataset of in-the-wild videos of unintentional action, as well as a suite of tasks for recognizing, localizing, and anticipating its onset. We train a supervised neural network as a baseline and analyze its performance compared to human consistency on the tasks. We also investigate self-supervised representations that leverage natural
more » ... als in our dataset, and show the effectiveness of an approach that uses the intrinsic speed of video to perform competitively with highly-supervised pretraining. However, a significant gap between machine and human performance remains. The project website is available at https://oops.cs.columbia.edu
arXiv:1911.11206v1 fatcat:gdiefmoe55eijah5h26tgxjoym