| 694 |
BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics |
2020 |
VLDB |
0.00018031141 |
| 1,390 |
MIRIS: Fast Object Track Queries in Video |
2020 |
SIGMOD |
0.00012242018 |
| 1,655 |
Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine |
2019 |
CIDR |
0.000109771 |
| 2,536 |
DeepLens: Towards a Visual Data Management System |
2019 |
CIDR |
8.5817195e-05 |
| 2,759 |
Complaint-driven Training Data Debugging for Query 2.0 |
2020 |
SIGMOD |
8.1646193e-05 |
| 3,291 |
Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics |
2021 |
VLDB |
7.2607192e-05 |
| 3,409 |
End-to-end Optimization of Machine Learning Prediction Queries |
2022 |
SIGMOD |
7.1240791e-05 |
| 3,553 |
Approximate Selection with Guarantees using Proxies |
2020 |
VLDB |
6.9763548e-05 |
| 3,610 |
EVA: A Symbolic Approach to Accelerating Exploratory Video Analytics with Materialized Views |
2022 |
SIGMOD |
6.919859e-05 |
| 3,624 |
SVQ: Streaming Video Queries |
2019 |
SIGMOD |
6.9013718e-05 |
| 4,221 |
Vaas: Video Analytics At Scale |
2020 |
VLDB |
6.3414314e-05 |
| 4,265 |
VSS: A Storage System for Video Analytics |
2021 |
SIGMOD |
6.3012892e-05 |
| 4,492 |
TASTI: Semantic Indexes for Machine Learning-based Queries over Unstructured Data |
2022 |
SIGMOD |
6.1374891e-05 |
| 4,565 |
Optimizing Video Analytics with Declarative Model Relationships |
2023 |
VLDB |
6.0746821e-05 |
| 4,686 |
Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures |
2023 |
VLDB |
5.9929067e-05 |
| 4,703 |
Accelerating Approximate Aggregation Queries with Expensive Predicates |
2021 |
VLDB |
5.9793615e-05 |
| 4,749 |
ODIN: Automated Drift Detection and Recovery in Video Analytics |
2020 |
VLDB |
5.9428569e-05 |
| 4,865 |
OTIF: Efficient Tracker Pre-processing over Large Video Datasets |
2022 |
SIGMOD |
5.8627966e-05 |
| 4,909 |
A Method for Optimizing Opaque Filter Queries |
2020 |
SIGMOD |
5.8354189e-05 |
| 4,947 |
Evaluating Temporal Queries Over Video Feeds |
2021 |
SIGMOD |
5.8107138e-05 |
| 5,062 |
Optimizing Machine Learning Inference Queries with Correlative Proxy Models |
2022 |
VLDB |
5.7172262e-05 |
| 5,168 |
FiGO: Fine-Grained Query Optimization in Video Analytics |
2022 |
SIGMOD |
5.6446115e-05 |
| 5,232 |
Zeus: Efficiently Localizing Actions in Videos using Reinforcement Learning |
2022 |
SIGMOD |
5.6094155e-05 |
| 5,528 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
5.4571136e-05 |
| 6,122 |
VOCAL: Video Organization and Interactive Compositional AnaLytics |
2022 |
CIDR |
5.1966758e-05 |
| 6,184 |
Top-K Deep Video Analytics: A Probabilistic Approach |
2021 |
SIGMOD |
5.1636368e-05 |
| 6,242 |
Optimizing In-memory Database Engine for AI-powered On-line Decision Augmentation Using Persistent Memory |
2021 |
VLDB |
5.1351431e-05 |
| 6,278 |
The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward |
2021 |
VLDB |
5.1241654e-05 |
| 6,282 |
Mixer: Efficiently Understanding and Retrieving Visual Content at Web-scale |
2021 |
VLDB |
5.1235353e-05 |
| 6,306 |
Seiden: Revisiting Query Processing in Video Database Systems |
2023 |
VLDB |
5.1146055e-05 |
| 6,590 |
Interactive Demonstration of Probabilistic Predicates |
2018 |
SIGMOD |
4.996343e-05 |
| 6,868 |
Extract-Transform-Load for Video Streams |
2023 |
VLDB |
4.8982283e-05 |
| 7,246 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
4.7847433e-05 |
| 7,278 |
Sia: Optimizing Queries using Learned Predicates |
2021 |
SIGMOD |
4.7720613e-05 |
| 7,807 |
Scaling a Declarative Cluster Manager Architecture with Query Optimization Techniques |
2023 |
VLDB |
4.6417687e-05 |
| 8,280 |
DeepVQL: Deep Video Queries on PostgreSQL |
2023 |
VLDB |
4.5392079e-05 |
| 8,382 |
EQUI-VOCAL: Synthesizing Queries for Compositional Video Events from Limited User Interactions |
2023 |
VLDB |
4.5263687e-05 |
| 8,464 |
Semantic Operators and Their Optimization: Enabling LLM-Based Data Processing with Accuracy Guarantees in LOTUS |
2025 |
VLDB |
4.5003888e-05 |
| 8,646 |
Optimizing Video Selection LIMIT Queries With Commonsense Knowledge |
2024 |
VLDB |
4.4720866e-05 |
| 8,829 |
A Distributed System for Large-scale n-gram Language Models at Tencent |
2019 |
VLDB |
4.4364351e-05 |
| 9,049 |
JENNER: Just-in-time Enrichment in Query Processing |
2022 |
VLDB |
4.3997447e-05 |
| 9,311 |
On Efficient Approximate Queries over Machine Learning Models |
2023 |
VLDB |
4.3535588e-05 |
| 9,346 |
SketchQL: Video Moment Querying with a Visual Query Interface |
2024 |
SIGMOD |
4.3512358e-05 |
| 9,677 |
Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving |
2025 |
SIGMOD |
4.3006524e-05 |
| 9,771 |
VOCALExplore: Pay-as-You-Go Video Data Exploration and Model Building |
2023 |
VLDB |
4.2815042e-05 |
| 9,772 |
Everest: A Top-K Deep Video Analytics System |
2022 |
SIGMOD |
4.2815042e-05 |
| 9,788 |
Demonstration of Accelerating Machine Learning Inference Queries with Correlative Proxy Models |
2022 |
VLDB |
4.2799988e-05 |
| 10,064 |
Cut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,187 |
On Efficient Approximate Aggregate Nearest Neighbor Queries over Learned Representations |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,215 |
Task Cascades for Efficient Unstructured Data Processing |
2026 |
SIGMOD |
4.1905499e-05 |