High-Throughput Ingestion for Video Warehouse: Comprehensive Configuration and Effective Exploration
Summary: Hippo enables real-time video ingestion via V-ETL, reframing analytics as a data-warehouse task for hundreds of streams. It defines a 1e7x larger configuration space, accuracy-aware search with graph embeddings and RL, plus clustering with MILP to maximize accuracy under latency, delivering 300 streams with >30% gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Baiyan Zhang (Zhejiang University)
- 2. Zepeng Li (Zhejiang University)
- 3. Dongxiang Zhang (Zhejiang University)
- 4. Huan Li (Zhejiang University)
- 5. Kian-Lee Tan (National University of Singapore)
- 6. Gang Chen (Zhejiang University)
BibTeX Citation
@inproceedings{zhang_sigmod25,
title = {{High-Throughput Ingestion for Video Warehouse: Comprehensive Configuration and Effective Exploration}},
author = {Zhang, Baiyan and Li, Zepeng and Zhang, Dongxiang and Li, Huan and Tan, Kian-Lee and Chen, Gang},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725407},
url = {https://dl.acm.org/doi/10.1145/3725407},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,600 | Query-Aware Path Inference from Spatial Videos | 2026 | SIGMOD | 4.9769913e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,717 | Towards Effective Indexing for Very Large Video Sequence Database | 2005 | SIGMOD |
| 2 | 1,542 | HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics | 2016 | VLDB |
| 3 | 3,411 | Spatial and Temporal Constrained Ranked Retrieval over Videos | 2022 | VLDB |
| 4 | 11,219 | Scalable Complex Event Processing on Video Streams | 2025 | SIGMOD |
| 5 | 11,318 | Deja Vu: Efficient Video-Language Query Engine with Learning-based Inter-Frame Computation Reuse | 2025 | VLDB |
| 6 | 10,111 | TVM: A Tile-based Video Management Framework | 2024 | VLDB |
| 7 | 3,947 | OTIF: Efficient Tracker Pre-processing over Large Video Datasets | 2022 | SIGMOD |
| 8 | 7,010 | Video-zilla: An Indexing Layer for Large-Scale Video Analytics | 2022 | SIGMOD |
| 9 | 11,515 | Predictive and Near-Optimal Sampling for View Materialization in Video Databases | 2024 | SIGMOD |
| 10 | 6,586 | Extract-Transform-Load for Video Streams | 2023 | VLDB |