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Technical Report: Temporal Aggregate Representations

About

This technical report extends our work presented in [9] with more experiments. In [9], we tackle long-term video understanding, which requires reasoning from current and past or future observations and raises several fundamental questions. How should temporal or sequential relationships be modelled? What temporal extent of information and context needs to be processed? At what temporal scale should they be derived? [9] addresses these questions with a flexible multi-granular temporal aggregation framework. In this report, we conduct further experiments with this framework on different tasks and a new dataset, EPIC-KITCHENS-100.

Fadime Sener, Dibyadip Chatterjee, Angela Yao• 2021

Related benchmarks

TaskDatasetResultRank
Action AnticipationEPIC-KITCHENS 100 (test)
Overall Action Top-5 Recall12.6
59
Action AnticipationEpic-Kitchens-100 (val)
mCR@5 (Overall Verb)24.2
33
Action ClassificationEpic Kitchens 100
Top-1 Verb Accuracy59.9
22
Video ClassificationEpic Kitchens 100
Verb Accuracy66
8
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