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Guided Attention for Next Active Object @ EGO4D STA Challenge

A Guided-Attention mechanism enhances spatiotemporal feature extraction for short-term anticipation in egocentric videos, achieving state-of-the-art results using StillFast.

Year
2023
Venue
arXiv 2023
Authors
5
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arxiv.org/abs/2305.16066v3ARXIV-DEFAULT
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Abstract

In this technical report, we describe the Guided-Attention mechanism based solution for the short-term anticipation (STA) challenge for the EGO4D challenge. It combines the object detections, and the spatiotemporal features extracted from video clips, enhancing the motion and contextual information, and further decoding the object-centric and motion-centric information to address the problem of STA in egocentric videos. For the challenge, we build our model on top of StillFast with Guided Attention applied on fast network. Our model obtains better performance on the validation set and also achieves state-of-the-art (SOTA) results on the challenge test set for EGO4D Short-Term Object Interaction Anticipation Challenge.

Authors

5