Microalgae, vital for ecological balance and economic sectors, present challenges in detection due to their diverse sizes and conditions. This paper summarizes the second "Vision Meets Algae" (VisAlgae 2023) Challenge, aiming to enhance high-throughput microalgae cell detection. The challenge, which attracted 369 participating teams, includes a dataset of 1000 images across six classes, featuring microalgae of varying sizes and distinct features. Participants faced tasks such as detecting small targets, handling motion blur, and complex backgrounds. The top 10 methods, outlined here, offer insights into overcoming these challenges and maximizing detection accuracy. This intersection of algae research and computer vision offers promise for ecological understanding and technological advancement. The dataset can be accessed at: https://github.com/juntaoJianggavin/Visalgae2023/.
@article{arxiv.2505.20687,
title = {VisAlgae 2023: A Dataset and Challenge for Algae Detection in Microscopy Images},
author = {Mingxuan Sun and Juntao Jiang and Zhiqiang Yang and Shenao Kong and Jiamin Qi and Jianru Shang and Shuangling Luo and Wanfa Sun and Tianyi Wang and Yanqi Wang and Qixuan Wang and Tingjian Dai and Tianxiang Chen and Jinming Zhang and Xuerui Zhang and Yuepeng He and Pengcheng Fu and Qiu Guan and Shizheng Zhou and Yanbo Yu and Qigui Jiang and Teng Zhou and Liuyong Shi and Hong Yan},
journal= {arXiv preprint arXiv:2505.20687},
year = {2025}
}