mlsanityData to 7 Oct 2026

TransAction: ICL-SJTU Submission to EPIC-Kitchens Action Anticipation Challenge 2021

arXiv 2107.13259 ↗First posted 28 Jul 2021cs.CVcited by 6

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Abstract (arXiv)

In this report, the technical details of our submission to the EPIC-Kitchens Action Anticipation Challenge 2021 are given. We developed a hierarchical attention model for action anticipation, which leverages Transformer-based attention mechanism to aggregate features across temporal dimension, modalities, symbiotic branches respectively. In terms of Mean Top-5 Recall of action, our submission with team name ICL-SJTU achieved 13.39% for overall testing set, 10.05% for unseen subsets and 11.88% for tailed subsets. Additionally, it is noteworthy that our submission ranked 1st in terms of verb class in all three (sub)sets.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 7 of its 10 references that are in the map. First posted on arXiv 28 Jul 2021.

Builds on

7 of 10 references.

References · 7

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  3. 2016Temporal Segment Networks: Towards Good Practices for Deep Action Recognitioncited by 899
  4. 2021Multi-Modal Fusion Transformer for End-to-End Autonomous Drivingcited by 372
  5. 2020Equalization Loss for Long-Tailed Object Recognitioncited by 285
  6. 2020The EPIC-KITCHENS Dataset: Collection, Challenges and Baselinescited by 221
  7. 2020Rolling-Unrolling LSTMs for Action Anticipation from First-Person Videocited by 119

Built on by

Cited by year

Citing papers per year: 2022: 3; 2023: 1; 2024: 2.

6 papers.

  1. 2023An Outlook into the Future of Egocentric Visioncited by 84
  2. 2022Interaction Region Visual Transformer for Egocentric Action Anticipationcited by 36
  3. 2022Predicting the Next Action by Modeling the Abstract Goalcited by 14
  4. 2024Human Action Anticipation: A Surveycited by 8
  5. 2024Intention Action Anticipation Model with Guide-Feedback Loop Mechanismcited by 1
  6. 2022Learning to Anticipate Future with Dynamic Context Removalcited by 0