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 |
|---|---|---|---|---|
| 10,393 | Query-Aware Path Inference from Spatial Videos | 2026 | SIGMOD | 5.093636e-05 |
Previous
Page 1 / 1
Next
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 |
|---|---|---|---|---|
| 295 | Accelerating Machine Learning Inference with Probabilistic Predicates | 2018 | SIGMOD | 0.00022238183 |
| 569 | BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics | 2020 | VLDB | 0.00016348191 |
| 1,042 | MIRIS: Fast Object Track Queries in Video | 2020 | SIGMOD | 0.00012451966 |
| 1,607 | Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine | 2019 | CIDR | 0.0001022751 |
| 2,933 | EVA: A Symbolic Approach to Accelerating Exploratory Video Analytics with Materialized Views | 2022 | SIGMOD | 7.9474026e-05 |
| 3,410 | SVQ: Streaming Video Queries | 2019 | SIGMOD | 7.4362585e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,213 | SVQ++: Querying for Object Interactions in Video Streams | 2020 | SIGMOD |
| 2 | 4,991 | VisualWorldDB: A DBMS for the Visual World | 2020 | CIDR |
| 3 | 9,464 | Self-Enhancing Video Data Management System for Compositional Events with Large Language Models | 2025 | SIGMOD |
| 4 | 4,429 | Evaluating Temporal Queries Over Video Feeds | 2021 | SIGMOD |
| 5 | 11,548 | DeepO: A Learned Query Optimizer | 2022 | SIGMOD |
| 6 | 9,408 | SketchQL: Video Moment Querying with a Visual Query Interface | 2024 | SIGMOD |
| 7 | 2,384 | DeepLens: Towards a Visual Data Management System | 2019 | CIDR |
| 8 | 11,268 | Optimizing Video Queries with Declarative Clues | 2024 | VLDB |
| 9 | 3,410 | SVQ: Streaming Video Queries | 2019 | SIGMOD |
| 10 | 9,925 | DoveDB: A Declarative and Low-Latency Video Database | 2023 | VLDB |