# OysterSim: Underwater Simulation for Enhancing Oyster Reef Monitoring

arXiv: https://arxiv.org/abs/2209.09395 · HTML: https://mlsanity.com/paper/2209.09395/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Sep 2022.

## Built on by (most cited first, 9 of 9)

- [SeaDroneSim: Simulation of Aerial Images for Detection of Objects Above Water](https://mlsanity.com/paper/2210.16107/) (2022)
- [Whale Detection Enhancement through Synthetic Satellite Images](https://mlsanity.com/paper/2308.07766/) (2023)
- [MARVIS: Motion & Geometry Aware Real and Virtual Image Segmentation](https://mlsanity.com/paper/2403.09850/) (2024)
- [Detecting Olives with Synthetic or Real Data? Olive the Above](https://mlsanity.com/paper/2308.08271/) (2023)
- [DREAM: Domain-aware Reasoning for Efficient Autonomous Underwater Monitoring](https://mlsanity.com/paper/2509.13666/) (2025)
- [uScenes: A Multimodal RGB and 3D Sonar Dataset for Underwater Robot Perception](https://mlsanity.com/paper/2608.27795/) (2026)
- [Is AI currently capable of identifying wild oysters? A comparison of human annotators against the AI model, ODYSSEE](https://mlsanity.com/paper/2505.03108/) (2025)
- [EREBUS: End-to-end Robust Event Based Underwater Simulation](https://mlsanity.com/paper/2511.01381/) (2025)
- [UEOF: A Benchmark Dataset for Underwater Event-Based Optical Flow](https://mlsanity.com/paper/2601.10054/) (2026)

## Abstract (arXiv)

Oysters are the living vacuum cleaners of the oceans. There is an exponential decline in the oyster population due to over-harvesting. With the current development of the automation and AI, robots are becoming an integral part of the environmental monitoring process that can be also utilized for oyster reef preservation. Nevertheless, the underwater environment poses many difficulties, both from the practical - dangerous and time consuming operations, and the technical perspectives - distorted perception and unreliable navigation. To this end, we present a simulated environment that can be used to improve oyster reef monitoring. The simulated environment can be used to create photo-realistic image datasets with multiple sensor data and ground truth location of a remotely operated vehicle(ROV). Currently, there are no photo-realistic image datasets for oyster reef monitoring. Thus, we want to provide a new benchmark suite to the underwater community.