A challenging Video Question Answering (VQA) Benchmark based on real-world traffic scenes.
Updates:
Jul 2021
The dataset is publicly released. You may request download now.Jun 2021
The dataset usage details are available now.May 2021
The dataset homepage is live now.Feb 2021
The dataset is available upon email request.
Our paper at CVPR 2021, SUTD-TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic Events, is available at: [CVF Open Access], [arXiv:2103.15538], and [ResearchGate].
- Annotation Example examples/annotation_sample.jsonl
- Jsonl Reader Example examples/jsonl_reader.py
- Appearance Feature Preprocessing examples/preprocess_video_appearance_example.py
- Motion Feature Preprocessing examples/preprocess_video_motion_example.py
- Dataloader examples/dataloader_example.py
- Download Dataset
@InProceedings{Xu_2021_CVPR,
author = {Xu, Li and Huang, He and Liu, Jun},
title = {{SUTD-TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning Over Traffic Events}},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2021},
pages = {9878-9888}
}
Contributors: Lin Yutian, Tran Nguyen Bao Long, Liu Renhang, Qiao Yingjie, Xun Long Ng, Koh Kai Ting, Christabel Dorothy
Code Reference: thaolmk54 / hcrn-videoqa
li_xu [AT] mymail.sutd.edu.sg
he_huang [AT] mymail.sutd.edu.sg