Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine
Summary: Identifies cost and deployment pain in DNN video analytics and presents BlazeIt—an optimizing engine with FrameQL to automate and scale video-analytics pipelines. Demos FrameQL plus ML-debugging and optimizer primitives to make large-scale video queries feasible and outlines remaining systems challenges. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Daniel Kang
- 2. Peter Bailis
- 3. Matei Zaharia
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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 |
|---|---|---|---|---|
| 316 | NoScope: Optimizing Neural Network Queries over Video at Scale | 2017 | VLDB | 0.00027988668 |
| 329 | Accelerating Machine Learning Inference with Probabilistic Predicates | 2018 | SIGMOD | 0.00027249545 |
| 330 | The Query By Image Content (QBIC) System | 1995 | SIGMOD | 0.00027229588 |
| 2,495 | STRG-Index: Spatio-Temporal Region Graph Indexing for Large Video Databases | 2005 | SIGMOD | 8.6488427e-05 |
| 2,533 | DeepLens: Towards a Visual Data Management System | 2019 | CIDR | 8.5899934e-05 |
| 5,370 | Kyrix: Interactive Visual Data Exploration at Scale | 2019 | CIDR | 5.5432976e-05 |
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| 696 | BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics | 2020 | VLDB | 0.00018048935 |