| 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 |
| 1,657 |
Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine |
2019 |
CIDR |
0.00010987105 |
| 2,533 |
DeepLens: Towards a Visual Data Management System |
2019 |
CIDR |
8.5899934e-05 |
| 2,753 |
Complaint-driven Training Data Debugging for Query 2.0 |
2020 |
SIGMOD |
8.1724339e-05 |
| 3,293 |
Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics |
2021 |
VLDB |
7.2629834e-05 |
| 3,407 |
End-to-end Optimization of Machine Learning Prediction Queries |
2022 |
SIGMOD |
7.1295646e-05 |
| 3,558 |
Approximate Selection with Guarantees using Proxies |
2020 |
VLDB |
6.9765724e-05 |
| 3,606 |
EVA: A Symbolic Approach to Accelerating Exploratory Video Analytics with Materialized Views |
2022 |
SIGMOD |
6.9260354e-05 |
| 3,620 |
SVQ: Streaming Video Queries |
2019 |
SIGMOD |
6.9084299e-05 |
| 4,225 |
Vaas: Video Analytics At Scale |
2020 |
VLDB |
6.3469943e-05 |
| 4,269 |
VSS: A Storage System for Video Analytics |
2021 |
SIGMOD |
6.306798e-05 |
| 4,501 |
TASTI: Semantic Indexes for Machine Learning-based Queries over Unstructured Data |
2022 |
SIGMOD |
6.137686e-05 |
| 4,567 |
Optimizing Video Analytics with Declarative Model Relationships |
2023 |
VLDB |
6.080526e-05 |
| 4,687 |
Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures |
2023 |
VLDB |
5.9986055e-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 |
| 4,865 |
OTIF: Efficient Tracker Pre-processing over Large Video Datasets |
2022 |
SIGMOD |
5.8684353e-05 |
| 4,909 |
A Method for Optimizing Opaque Filter Queries |
2020 |
SIGMOD |
5.8338804e-05 |
| 4,950 |
Evaluating Temporal Queries Over Video Feeds |
2021 |
SIGMOD |
5.8104133e-05 |
| 5,072 |
Optimizing Machine Learning Inference Queries with Correlative Proxy Models |
2022 |
VLDB |
5.7185674e-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 |
| 5,645 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
5.3923454e-05 |
| 6,130 |
VOCAL: Video Organization and Interactive Compositional AnaLytics |
2022 |
CIDR |
5.1962107e-05 |
| 6,182 |
Top-K Deep Video Analytics: A Probabilistic Approach |
2021 |
SIGMOD |
5.1682689e-05 |
| 6,247 |
Optimizing In-memory Database Engine for AI-powered On-line Decision Augmentation Using Persistent Memory |
2021 |
VLDB |
5.1389201e-05 |
| 6,261 |
The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward |
2021 |
VLDB |
5.1350714e-05 |
| 6,285 |
Mixer: Efficiently Understanding and Retrieving Visual Content at Web-scale |
2021 |
VLDB |
5.1280578e-05 |
| 6,315 |
Seiden: Revisiting Query Processing in Video Database Systems |
2023 |
VLDB |
5.1142298e-05 |
| 6,590 |
Interactive Demonstration of Probabilistic Predicates |
2018 |
SIGMOD |
5.0010949e-05 |
| 6,877 |
Extract-Transform-Load for Video Streams |
2023 |
VLDB |
4.8974054e-05 |
| 7,251 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
4.7890519e-05 |
| 7,283 |
Sia: Optimizing Queries using Learned Predicates |
2021 |
SIGMOD |
4.7764688e-05 |
| 7,805 |
Scaling a Declarative Cluster Manager Architecture with Query Optimization Techniques |
2023 |
VLDB |
4.6462265e-05 |
| 8,287 |
DeepVQL: Deep Video Queries on PostgreSQL |
2023 |
VLDB |
4.5435639e-05 |
| 8,383 |
EQUI-VOCAL: Synthesizing Queries for Compositional Video Events from Limited User Interactions |
2023 |
VLDB |
4.5307128e-05 |
| 8,469 |
Semantic Operators and Their Optimization: Enabling LLM-Based Data Processing with Accuracy Guarantees in LOTUS |
2025 |
VLDB |
4.5041113e-05 |
| 8,672 |
Optimizing Video Selection LIMIT Queries With Commonsense Knowledge |
2024 |
VLDB |
4.4710897e-05 |
| 8,829 |
A Distributed System for Large-scale n-gram Language Models at Tencent |
2019 |
VLDB |
4.4406886e-05 |
| 9,049 |
JENNER: Just-in-time Enrichment in Query Processing |
2022 |
VLDB |
4.4039656e-05 |
| 9,341 |
SketchQL: Video Moment Querying with a Visual Query Interface |
2024 |
SIGMOD |
4.3554097e-05 |
| 9,351 |
On Efficient Approximate Queries over Machine Learning Models |
2023 |
VLDB |
4.3524472e-05 |
| 9,677 |
Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving |
2025 |
SIGMOD |
4.3047774e-05 |
| 9,769 |
VOCALExplore: Pay-as-You-Go Video Data Exploration and Model Building |
2023 |
VLDB |
4.2856106e-05 |
| 9,770 |
Everest: A Top-K Deep Video Analytics System |
2022 |
SIGMOD |
4.2856106e-05 |
| 9,807 |
Demonstration of Accelerating Machine Learning Inference Queries with Correlative Proxy Models |
2022 |
VLDB |
4.2805224e-05 |
| 10,064 |
Cut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,187 |
On Efficient Approximate Aggregate Nearest Neighbor Queries over Learned Representations |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,215 |
Task Cascades for Efficient Unstructured Data Processing |
2026 |
SIGMOD |
4.1945683e-05 |