What will Happen Next? Forecasting Player Moves in Sports Videos

By Panna Felsen, Pulkit Agrawal, Jitendra Malik. 2017

81 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing

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Citations in the corpus

SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference (2018, background): “The question of ‘what will happen next?’ has also been studied in photo albums (Huang et al., 2016), videos of team sports, (Felsen et al., 2017) and egocentric dog videos (Ehsani et al., 2018).”
From Recognition to Cognition: Visual Commonsense Reasoning (2018, neutral): “Commonsense Reasoning Our task unifies work involving reasoning about commonsense phenomena, such as physics [54, 84], social interactions [2, 77, 12, 27], procedure understanding [91, 3] and predicting what might happen next in a video [74, 17, 92, 78, 18, 64, 85].”
Stochastic Prediction of Multi-Agent Interactions from Partial Observations (2019, methodology): “The visual only baseline predicts all 4 future steps based on last observed visual feature, as is in Felsen et al. (2017).”
Rolling-Unrolling LSTMs for Action Anticipation from First-Person Video (2020, background): “Felsen et al. [55] developed a framework to forecast future events in team sports video from visual input.”
MECCANO: A Multimodal Egocentric Dataset for Humans Behavior Understanding in the Industrial-like Domain (2022, background): “The authors of [31] proposed a generic framework for forecasting future events in team sports videos related to water polo and basketball events.”
Future Event Prediction: If and When (2019, background): “Our work is significantly different in that i) we predict whether the event will happen or not ii) we give time estimate to say when the event is likely to happen and with what probability iii) we predict significantly longer time horizon (up to 10 seconds) and iv) we don’t require static and normal”
VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation (2020, background): “Beyond the autonomous driving domain, there is more general interest to predict the intents of interacting agents, such as for pedestrians [2, 13, 24], human activities [28] or for sports players [12, 26, 32, 33].”
What Would You Expect? Anticipating Egocentric Actions With Rolling-Unrolling LSTMs and Modality Attention (2019, background): “Previous works investigated different forms of action and activity anticipation from third person video [1, 15, 18, 25, 27, 28, 31, 32, 33, 40, 58, 64].”
When will you do what? - Anticipating Temporal Occurrences of Activities (2018, background): “Recently, a framework has been introduced in [2] to predict the next move of players or the location of the ball in the immediate future from sports videos.”