CoralVQA: A Large-Scale Visual Question Answering Dataset for Coral Reef Image Understanding

TL;DR

CoralVQA introduces a large-scale, domain-specific VQA dataset for coral reef images, enabling advanced ecological analysis and supporting conservation efforts through vision-language reasoning.

Contribution

This paper presents the first extensive coral reef VQA dataset, CoralVQA, with a semi-automatic construction process involving marine biologists, addressing domain-specific challenges.

Findings

State-of-the-art LVLMs face limitations on coralVQA

CoralVQA enables comprehensive ecological question answering

Benchmark results highlight future research directions

Abstract

Coral reefs are vital yet vulnerable ecosystems that require continuous monitoring to support conservation. While coral reef images provide essential information in coral monitoring, interpreting such images remains challenging due to the need for domain expertise. Visual Question Answering (VQA), powered by Large Vision-Language Models (LVLMs), has great potential in user-friendly interaction with coral reef images. However, applying VQA to coral imagery demands a dedicated dataset that addresses two key challenges: domain-specific annotations and multidimensional questions. In this work, we introduce CoralVQA, the first large-scale VQA dataset for coral reef analysis. It contains 12,805 real-world coral images from 67 coral genera collected from 3 oceans, along with 277,653 question-answer pairs that comprehensively assess ecological and health-related conditions. To construct this dataset, we develop a semi-automatic data construction pipeline in collaboration with marine biologists to ensure both scalability and professional-grade data quality. CoralVQA presents novel challenges and provides a comprehensive benchmark for studying vision-language reasoning in the context of coral reef images. By evaluating several state-of-the-art LVLMs, we reveal key limitations and opportunities. These insights form a foundation for future LVLM development, with a particular emphasis on supporting coral conservation efforts.