StereoAdapter: Adapting Stereo Depth Estimation to
Underwater Scenes
Zhengri Wu1*
Yiran Wang2*
Yu Wen1*
Zeyu Zhang3*†
Biao Wu1
Hao Tang3‡
1 AI Geeks
2 Australian Centre for Robotics
3 Peking University
* Equal contribution.
† Project lead.
‡ Corresponding author.
[Paper]
[Code]
[Dataset]
[Model]
TL;DR: StereoAdapter is a self-supervised adaptive model that allows robust underwater depth estimation.
Real World Results
We evaluate StereoAdapter on a BlueROV2 across three obstacle layouts and three motion trajectories.
Layout #1
Layout #2
Layout #3
Method
Detailed architecture of the StereoAdapter: (a) two-stage self-supervised training pipeline; (b) update mechanism with LoRA.
Benchmark Results
Visualization results of Stereo Depth Estimation Methods on SQUID and TartanAir.
UW-StereoDepth-40K
Example from the high-quality UW-StereoDepth-40K dataset.
StereoAdapter: Adapting Stereo Depth Estimation to Underwater Scenes