DeepVQL: Deep Video Queries on PostgreSQL
Summary: DeepVQL extends PostgreSQL with declarative video-database functions and UDFs for deep-learning-based object detection, tracking, and analytics. Its distinctive capability is querying moving objects under explicit spatial-region and temporal-duration predicates in traffic videos. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dong June Lew (Kunsan National University)
- 2. Kihyun Yoo (Kunsan National University)
- 3. Kwang Woo Nam (Kunsan National University)
BibTeX Citation
@article{lew_vldb23,
title = {{DeepVQL: Deep Video Queries on PostgreSQL}},
author = {Lew, Dong June and Yoo, Kihyun and Nam, Kwang Woo},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {12},
pages = {3910--3913},
doi = {10.14778/3611540.3611583},
url = {https://doi.org/10.14778/3611540.3611583},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,589 | Query-Aware Path Inference from Spatial Videos | 2026 | SIGMOD | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 281 | Accelerating Machine Learning Inference with Probabilistic Predicates | 2018 | SIGMOD | 0.00022295232 |
| 541 | BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics | 2020 | VLDB | 0.00016657685 |
| 1,024 | MIRIS: Fast Object Track Queries in Video | 2020 | SIGMOD | 0.00012430491 |
| 1,617 | Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine | 2019 | CIDR | 0.00010057464 |
| 2,787 | EVA: A Symbolic Approach to Accelerating Exploratory Video Analytics with Materialized Views | 2022 | SIGMOD | 8.0158999e-05 |
| 3,429 | SVQ: Streaming Video Queries | 2019 | SIGMOD | 7.306047e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,286 | SVQ++: Querying for Object Interactions in Video Streams | 2020 | SIGMOD |
| 2 | 5,026 | VisualWorldDB: A DBMS for the Visual World | 2020 | CIDR |
| 3 | 9,645 | Self-Enhancing Video Data Management System for Compositional Events with Large Language Models | 2025 | SIGMOD |
| 4 | 4,495 | Evaluating Temporal Queries Over Video Feeds | 2021 | SIGMOD |
| 5 | 11,857 | DeepO: A Learned Query Optimizer | 2022 | SIGMOD |
| 6 | 9,589 | SketchQL: Video Moment Querying with a Visual Query Interface | 2024 | SIGMOD |
| 7 | 2,391 | DeepLens: Towards a Visual Data Management System | 2019 | CIDR |
| 8 | 11,596 | Optimizing Video Queries with Declarative Clues | 2024 | VLDB |
| 9 | 3,429 | SVQ: Streaming Video Queries | 2019 | SIGMOD |
| 10 | 9,541 | DoveDB: A Declarative and Low-Latency Video Database | 2023 | VLDB |