# Technical Report for CVPR 2022 LOVEU AQTC Challenge

arXiv: https://arxiv.org/abs/2206.14555 · HTML: https://mlsanity.com/paper/2206.14555/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 9 references that are in the map.
- First posted on arXiv 29 Jun 2022.

## Builds on (most cited first, 9 of 9)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [VQA: Visual Question Answering](https://mlsanity.com/paper/1505.00468/) (2015)
- [Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling](https://mlsanity.com/paper/1412.3555/) (2014)
- [Visual Dialog](https://mlsanity.com/paper/1611.08669/) (2016)
- [Embodied Question Answering](https://mlsanity.com/paper/1711.11543/) (2017)
- [Audio-Visual Scene-Aware Dialog](https://mlsanity.com/paper/1901.09107/) (2019)
- [Multi-Target Embodied Question Answering](https://mlsanity.com/paper/1904.04686/) (2019)
- [AssistQ: Affordance-centric Question-driven Task Completion for Egocentric Assistant](https://mlsanity.com/paper/2203.04203/) (2022)

## Abstract (arXiv)

This technical report presents the 2nd winning model for AQTC, a task newly introduced in CVPR 2022 LOng-form VidEo Understanding (LOVEU) challenges. This challenge faces difficulties with multi-step answers, multi-modal, and diverse and changing button representations in video. We address this problem by proposing a new context ground module attention mechanism for more effective feature mapping. In addition, we also perform the analysis over the number of buttons and ablation study of different step networks and video features. As a result, we achieved the overall 2nd place in LOVEU competition track 3, specifically the 1st place in two out of four evaluation metrics. Our code is available at https://github.com/jaykim9870/ CVPR-22_LOVEU_unipyler.