# The Fishnet Open Images Database: A Dataset for Fish Detection and Fine-Grained Categorization in Fisheries

arXiv: https://arxiv.org/abs/2106.09178 · HTML: https://mlsanity.com/paper/2106.09178/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 36 references that are in the map.
- First posted on arXiv 16 Jun 2021.

## Builds on (most cited first, 10 of 10)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Rethinking the Inception Architecture for Computer Vision](https://mlsanity.com/paper/1512.00567/) (2015)
- [Feature Pyramid Networks for Object Detection](https://mlsanity.com/paper/1612.03144/) (2016)
- [Recognition in Terra Incognita](https://mlsanity.com/paper/1807.04975/) (2018)
- [A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay](https://mlsanity.com/paper/1803.09820/) (2018)
- [A Realistic Fish-Habitat Dataset to Evaluate Algorithms for Underwater Visual Analysis](https://mlsanity.com/paper/2008.12603/) (2020)
- [The iWildCam 2019 Challenge Dataset](https://mlsanity.com/paper/1907.07617/) (2019)
- [Video-based Hierarchical Species Classification for Longline Fishing Monitoring](https://mlsanity.com/paper/2102.03520/) (2021)

## Built on by (most cited first, 7 of 7)

- [AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis](https://mlsanity.com/paper/2502.01785/) (2025)
- [AutoFish: Dataset and Benchmark for Fine-grained Analysis of Fish](https://mlsanity.com/paper/2501.03767/) (2025)
- [Composing Open-domain Vision with RAG for Ocean Monitoring and Conservation](https://mlsanity.com/paper/2412.02262/) (2024)
- [FishNet++: Analyzing the capabilities of Multimodal Large Language Models in marine biology](https://mlsanity.com/paper/2509.25564/) (2025)
- [AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock](https://mlsanity.com/paper/2507.22101/) (2025)
- [Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners](https://mlsanity.com/paper/2511.15468/) (2025)
- [M3-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering](https://mlsanity.com/paper/2604.25122/) (2026)

## Abstract (arXiv)

Camera-based electronic monitoring (EM) systems are increasingly being deployed onboard commercial fishing vessels to collect essential data for fisheries management and regulation. These systems generate large quantities of video data which must be reviewed on land by human experts. Computer vision can assist this process by automatically detecting and classifying fish species, however the lack of existing public data in this domain has hindered progress. To address this, we present the Fishnet Open Images Database, a large dataset of EM imagery for fish detection and fine-grained categorization onboard commercial fishing vessels. The dataset consists of 86,029 images containing 34 object classes, making it the largest and most diverse public dataset of fisheries EM imagery to-date. It includes many of the characteristic challenges of EM data: visual similarity between species, skewed class distributions, harsh weather conditions, and chaotic crew activity. We evaluate the performance of existing detection and classification algorithms and demonstrate that the dataset can serve as a challenging benchmark for development of computer vision algorithms in fisheries. The dataset is available at https://www.fishnet.ai/.