Team VI-I2R Technical Report on EPIC-Kitchens Action Anticipation Challenge 2020

Team VI-I2R Technical Report on EPIC-Kitchens Action Anticipation Challenge 2020
Title:
Team VI-I2R Technical Report on EPIC-Kitchens Action Anticipation Challenge 2020
Other Titles:
EPIC-Kitchens Challenges @CVPR2020, Virtual CVPR
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Publication Date:
26 June 2020
Citation:
Abstract:
In this report, we present our investigations on feature representation, hand mask modality, past action prediction, and model ensemble, for the EPIC-Kitchens Action Anticipation Challenge. Building upon an existing action anticipation model, i.e., RULSTM, our framework effectively utilizes enhanced feature representation, gives more emphasis on many-shot objects, and incorporates additional hand mask modality. We also explore a network modification to capture past action prediction. Furthermore, to exploit all the training data and aggregate the complementary information from different models, we employ model ensemble. We achieved top-1 action anticipation accuracy of 16.02% for Seen Kitchens (S1), and 10.11% for Unseen Kitchens (S2). Our submission, under the team name VI-I2R, achieved 2nd place for both seen and unseen kitchens, in terms of top-1 action anticipation accuracy.
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Funding Info:
This research is supported by the Agency for Science, Technology and Research (A*STAR) under its AME Programmatic Funding Scheme (Project #A18A2b0046) and the National Research Foundation, Singapore under its NRF-ISF Joint Call (Award NRF2015-NRF-ISF001-2541).
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