# 2rd Place Solutions in the HC-STVG track of Person in Context Challenge 2021

arXiv: https://arxiv.org/abs/2106.07166 · HTML: https://mlsanity.com/paper/2106.07166/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 9 references that are in the map.
- First posted on arXiv 14 Jun 2021.

## Builds on (most cited first, 6 of 6)

- [Mask R-CNN](https://mlsanity.com/paper/1703.06870/) (2017)
- [LXMERT: Learning Cross-Modality Encoder Representations from Transformers](https://mlsanity.com/paper/1908.07490/) (2019)
- [Simple Online and Realtime Tracking with a Deep Association Metric](https://mlsanity.com/paper/1703.07402/) (2017)
- [FastReID: A Pytorch Toolbox for General Instance Re-identification](https://mlsanity.com/paper/2006.02631/) (2020)
- [Human-centric Spatio-Temporal Video Grounding With Visual Transformers](https://mlsanity.com/paper/2011.05049/) (2020)
- [Deep Cosine Metric Learning for Person Re-Identification](https://mlsanity.com/paper/1812.00442/) (2018)

## Built on by (most cited first, 8 of 8)

- [Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding](https://mlsanity.com/paper/2109.04872/) (2021)
- [Context-Guided Spatio-Temporal Video Grounding](https://mlsanity.com/paper/2401.01578/) (2024)
- [Video-GroundingDINO: Towards Open-Vocabulary Spatio-Temporal Video Grounding](https://mlsanity.com/paper/2401.00901/) (2023)
- [SpaceVLLM: Endowing Multimodal Large Language Model with Spatio-Temporal Video Grounding Capability](https://mlsanity.com/paper/2503.13983/) (2025)
- [Knowing Your Target: Target-Aware Transformer Makes Better Spatio-Temporal Video Grounding](https://mlsanity.com/paper/2502.11168/) (2025)
- [STVGFormer: Spatio-Temporal Video Grounding with Static-Dynamic Cross-Modal Understanding](https://mlsanity.com/paper/2207.02756/) (2022)
- [Towards Long-Form Spatio-Temporal Video Grounding](https://mlsanity.com/paper/2602.23294/) (2026)
- [ScanFocus: A Coarse-to-Fine Framework for Spatio-Temporal Video Grounding](https://mlsanity.com/paper/2607.13421/) (2026)

## Abstract (arXiv)

In this technical report, we present our solution to localize a spatio-temporal person in an untrimmed video based on a sentence. We achieve the second vIOU(0.30025) in the HC-STVG track of the 3rd Person in Context(PIC) Challenge. Our solution contains three parts: 1) human attributes information is extracted from the sentence, it is helpful to filter out tube proposals in the testing phase and supervise our classifier to learn appearance information in the training phase. 2) we detect humans with YoloV5 and track humans based on the DeepSort framework but replace the original ReID network with FastReID. 3) a visual transformer is used to extract cross-modal representations for localizing a spatio-temporal tube of the target person.