# A Simple Transformer-Based Model for Ego4D Natural Language Queries Challenge

arXiv: https://arxiv.org/abs/2211.08704 · HTML: https://mlsanity.com/paper/2211.08704/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 12 references that are in the map.
- First posted on arXiv 16 Nov 2022.

## Builds on (most cited first, 11 of 11)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [SlowFast Networks for Video Recognition](https://mlsanity.com/paper/1812.03982/) (2018)
- [Ego4D: Around the World in 3,000 Hours of Egocentric Video](https://mlsanity.com/paper/2110.07058/) (2021)
- [Soft-NMS -- Improving Object Detection With One Line of Code](https://mlsanity.com/paper/1704.04503/) (2017)
- [ActionFormer: Localizing Moments of Actions with Transformers](https://mlsanity.com/paper/2202.07925/) (2022)
- [Egocentric Video-Language Pretraining](https://mlsanity.com/paper/2206.01670/) (2022)
- [Omnivore: A Single Model for Many Visual Modalities](https://mlsanity.com/paper/2201.08377/) (2022)
- [AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer](https://mlsanity.com/paper/2108.03647/) (2021)
- [A Survey on Temporal Sentence Grounding in Videos](https://mlsanity.com/paper/2109.08039/) (2021)
- [ReLER@ZJU-Alibaba Submission to the Ego4D Natural Language Queries Challenge 2022](https://mlsanity.com/paper/2207.00383/) (2022)

## Built on by (most cited first, 6 of 6)

- [NaQ: Leveraging Narrations as Queries to Supervise Episodic Memory](https://mlsanity.com/paper/2301.00746/) (2023)
- [GroundNLQ @ Ego4D Natural Language Queries Challenge 2023](https://mlsanity.com/paper/2306.15255/) (2023)
- [SpotEM: Efficient Video Search for Episodic Memory](https://mlsanity.com/paper/2306.15850/) (2023)
- [ObjectNLQ @ Ego4D Episodic Memory Challenge 2024](https://mlsanity.com/paper/2406.15778/) (2024)
- [Action Sensitivity Learning for the Ego4D Episodic Memory Challenge 2023](https://mlsanity.com/paper/2306.09172/) (2023)
- [Building Egocentric Procedural AI Assistant: Methods, Benchmarks, and Challenges](https://mlsanity.com/paper/2511.13261/) (2025)

## Abstract (arXiv)

This report describes Badgers@UW-Madison, our submission to the Ego4D Natural Language Queries (NLQ) Challenge. Our solution inherits the point-based event representation from our prior work on temporal action localization, and develops a Transformer-based model for video grounding. Further, our solution integrates several strong video features including SlowFast, Omnivore and EgoVLP. Without bells and whistles, our submission based on a single model achieves 12.64% Mean R@1 and is ranked 2nd on the public leaderboard. Meanwhile, our method garners 28.45% (18.03%) R@5 at tIoU=0.3 (0.5), surpassing the top-ranked solution by up to 5.5 absolute percentage points.