Back to papers
MAST: Towards Efficient Analytical Query Processing on Point Cloud Data
Summary: MAST enables approximate analytics on point clouds by sampling core frames under a budget to minimize DL calls. It fuses multi-agent RL sampling with a spatio-temporal index to accelerate PC retrieval and aggregates, with provable error bounds.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 7047
- Venue
- SIGMOD
- Year
- 2025
- Pagerank
- 4.1945683e-05
- Overall Rank
- 10,382 | 27.78%
- DOI
-
10.1145/3709702
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 333 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027206884 |
| 696 |
BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics |
2020 |
VLDB |
0.00018048935 |
| 1,388 |
MIRIS: Fast Object Track Queries in Video |
2020 |
SIGMOD |
0.00012260926 |
| 3,558 |
Approximate Selection with Guarantees using Proxies |
2020 |
VLDB |
6.9765724e-05 |
| 3,604 |
Spatial and Temporal Constrained Ranked Retrieval over Videos |
2022 |
VLDB |
6.9301368e-05 |
| 3,606 |
EVA: A Symbolic Approach to Accelerating Exploratory Video Analytics with Materialized Views |
2022 |
SIGMOD |
6.9260354e-05 |
| 4,176 |
Ganos: A Multidimensional, Dynamic, and Scene-Oriented Cloud-Native Spatial Database Engine |
2022 |
VLDB |
6.3837225e-05 |
| 4,501 |
TASTI: Semantic Indexes for Machine Learning-based Queries over Unstructured Data |
2022 |
SIGMOD |
6.137686e-05 |
| 4,641 |
VIVA: An End-to-End System for Interactive Video Analytics |
2022 |
CIDR |
6.027004e-05 |
| 4,712 |
Accelerating Approximate Aggregation Queries with Expensive Predicates |
2021 |
VLDB |
5.9787986e-05 |
| 4,751 |
ODIN: Automated Drift Detection and Recovery in Video Analytics |
2020 |
VLDB |
5.9485403e-05 |
| 4,909 |
A Method for Optimizing Opaque Filter Queries |
2020 |
SIGMOD |
5.8338804e-05 |
| 5,135 |
Zeus: Efficiently Localizing Actions in Videos using Reinforcement Learning |
2022 |
SIGMOD |
5.6724721e-05 |
| 5,173 |
FiGO: Fine-Grained Query Optimization in Video Analytics |
2022 |
SIGMOD |
5.6447253e-05 |
| 5,290 |
LightDB: A DBMS for Virtual Reality Video |
2018 |
VLDB |
5.5828169e-05 |
| 5,572 |
The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data |
2023 |
SIGMOD |
5.4277273e-05 |
| 6,315 |
Seiden: Revisiting Query Processing in Video Database Systems |
2023 |
VLDB |
5.1142298e-05 |
| 6,877 |
Extract-Transform-Load for Video Streams |
2023 |
VLDB |
4.8974054e-05 |
| 7,928 |
Accelerating Aggregation Queries on Unstructured Streams of Data |
2023 |
VLDB |
4.613455e-05 |
| 8,405 |
Towards Designing and Learning Piecewise Space-Filling Curves |
2023 |
VLDB |
4.5224126e-05 |
| 8,672 |
Optimizing Video Selection LIMIT Queries With Commonsense Knowledge |
2024 |
VLDB |
4.4710897e-05 |
| 9,354 |
Interactive Demonstration of EVA |
2023 |
VLDB |
4.3517085e-05 |
| 9,374 |
SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches |
2024 |
VLDB |
4.3479148e-05 |
| 9,751 |
Co-movement Pattern Mining from Videos |
2024 |
VLDB |
4.2897489e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 12,016 |
Effective Multi-Modal Retrieval based on Stacked Auto-Encoders |
2014 |
VLDB |
4.1945683e-05 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.9554751e-05 |
| 7,928 |
Accelerating Aggregation Queries on Unstructured Streams of Data |
2023 |
VLDB |
4.613455e-05 |
| 6,383 |
Sample-Efficient Cardinality Estimation Using Geometric Deep Learning |
2024 |
VLDB |
5.0884322e-05 |
| 10,103 |
Query-Aware Path Inference from Spatial Videos |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,944 |
Predictive and Near-Optimal Sampling for View Materialization in Video Databases |
2024 |
SIGMOD |
4.1945683e-05 |
| 4,950 |
Evaluating Temporal Queries Over Video Feeds |
2021 |
SIGMOD |
5.8104133e-05 |
| 8,293 |
Challenges and Opportunities for Autonomous Vehicle Query Systems |
2021 |
CIDR |
4.5435639e-05 |
| 9,120 |
Deep Query Optimization |
2019 |
SIGMOD |
4.392741e-05 |
| 10,437 |
Demonstrating MAST: An Efficient System for Point Cloud Data Analytics |
2025 |
SIGMOD |
4.1945683e-05 |