ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab

TL;DR

ProBio is a multimodal dataset with benchmarks designed to improve activity understanding in molecular biology labs, aiming to address reproducibility issues through AI-based monitoring.

Contribution

The paper introduces ProBio, a comprehensive multimodal dataset and benchmarks for activity recognition in BioLab environments, facilitating research on reproducibility and intelligent monitoring.

Findings

Current video understanding models have limitations in BioLab settings.

ProBio provides detailed annotations for activity analysis.

Benchmarks highlight challenges in multimodal activity recognition.

Abstract

The challenge of replicating research results has posed a significant impediment to the field of molecular biology. The advent of modern intelligent systems has led to notable progress in various domains. Consequently, we embarked on an investigation of intelligent monitoring systems as a means of tackling the issue of the reproducibility crisis. Specifically, we first curate a comprehensive multimodal dataset, named ProBio, as an initial step towards this objective. This dataset comprises fine-grained hierarchical annotations intended for the purpose of studying activity understanding in BioLab. Next, we devise two challenging benchmarks, transparent solution tracking and multimodal action recognition, to emphasize the unique characteristics and difficulties associated with activity understanding in BioLab settings. Finally, we provide a thorough experimental evaluation of contemporary video understanding models and highlight their limitations in this specialized domain to identify potential avenues for future research. We hope ProBio with associated benchmarks may garner increased focus on modern AI techniques in the realm of molecular biology.