The availability of vast video collections and the accuracy of ML models has generated
significant interest in video analytics systems. Since naively processing all frames using …

State-of-the-art video database management systems (VDBMSs) often use lightweight proxy
models to accelerate object retrieval and aggregate queries. The key assumption underlying …

Advances in ML have motivated the design of video analytics systems that allow for
structured queries over video datasets. However, existing systems limit query expressivity …

We introduce VOCALExplore, a system designed to support users in building domain-
specific models over video datasets. VOCALExplore supports interactive labeling sessions …

With the exponential growth of video data, there is a pressing need for efficient video
analysis technology. Modern query frameworks aim to accelerate queries by reducing the …

In recent years, deep learning models have revolutionized computer vision, enabling
diverse applications. However, these models are computationally expensive, and leveraging …

Numerous applications today rely on artificial intelligence over images. Image AI is,
however, extremely expensive. In particular, the inference cost of image AI dominates the …

In this demonstration, we will present EVA, an end-to-end AI-Relational database
management system. We will demonstrate the capabilities and utility of EVA using three …

Querying video data has become increasingly popular and useful. Video queries can be
complex, ranging from retrieval tasks (“find me the top videos that have...”), to analytics (“how …

Video analytics is widely used in contemporary systems and services. At the forefront of
video analytics are video queries that users develop to find objects of particular interest …