Controlled Intentional Degradation in Analytical Video Systems
Summary: Degradation-accuracy profiling to control privacy-aware video analytics, balancing accuracy and policy goals. Smokescreen prototype with limited-data curve estimation and profile repair; achieves tighter error bounds and more accurate tradeoffs across datasets, models, and queries. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wenjia He (University of Michigan)
- 2. Michael Cafarella (Massachusetts Institute of Technology)
BibTeX Citation
@inproceedings{he_sigmod22,
title = {{Controlled Intentional Degradation in Analytical Video Systems}},
author = {He, Wenjia and Cafarella, Michael},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3517899},
url = {https://dl.acm.org/doi/10.1145/3514221.3517899},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,362 | EQUI-VOCAL: Synthesizing Queries for Compositional Video Events from Limited User Interactions | 2023 | VLDB | 5.4432545e-05 |
| 8,589 | Optimizing Video Selection LIMIT Queries With Commonsense Knowledge | 2024 | VLDB | 5.4065627e-05 |
| 9,881 | The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format | 2024 | SIGMOD | 5.2040783e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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