PAINE Demo: Optimizing Video Selection Queries With Commonsense Knowledge
Summary: PAINE accelerates video selection queries with a lossy frame index and probabilistic commonsense models that infer unindexed video content. It predicts predicate-satisfying videos to avoid expensive detector execution, demonstrated against SCAN. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Wenjia He (University of Michigan)
- 2. Ibrahim Sabek (Massachusetts Institute of Technology)
- 3. Yuze Lou (University of Michigan)
- 4. Michael Cafarella (Massachusetts Institute of Technology)
BibTeX Citation
@article{he_vldb23,
title = {{PAINE Demo: Optimizing Video Selection Queries With Commonsense Knowledge}},
author = {He, Wenjia and Sabek, Ibrahim and Lou, Yuze and Cafarella, Michael},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {12},
pages = {3902--3905},
doi = {10.14778/3611540.3611581},
url = {https://doi.org/10.14778/3611540.3611581},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 284 | NoScope: Optimizing Neural Network Queries over Video at Scale | 2017 | VLDB | 0.00022370521 |
| 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 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 9,925 | DoveDB: A Declarative and Low-Latency Video Database | 2023 | VLDB |
| 2 | 7,176 | Interactive Demonstration of Probabilistic Predicates | 2018 | SIGMOD |
| 3 | 4,459 | Efficient and Cost-effective Techniques for Browsing and Indexing Large Video Databases | 2000 | SIGMOD |
| 4 | 9,421 | SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches | 2024 | VLDB |
| 5 | 4,375 | FiGO: Fine-Grained Query Optimization in Video Analytics | 2022 | SIGMOD |
| 6 | 5,789 | Seiden: Revisiting Query Processing in Video Database Systems | 2023 | VLDB |
| 7 | 9,408 | SketchQL: Video Moment Querying with a Visual Query Interface | 2024 | SIGMOD |
| 8 | 11,483 | EQUI-VOCAL Demonstration: Synthesizing Video Queries from User Interactions | 2023 | VLDB |
| 9 | 11,268 | Optimizing Video Queries with Declarative Clues | 2024 | VLDB |
| 10 | 8,589 | Optimizing Video Selection LIMIT Queries With Commonsense Knowledge | 2024 | VLDB |