StereoAdapter-2: Globally Structure-Consistent Underwater Stereo Depth Estimation

• URL: http://arxiv.org/abs/2602.16915v1
• Date: Wed, 18 Feb 2026 22:12:08 GMT
• Title: StereoAdapter-2: Globally Structure-Consistent Underwater Stereo Depth Estimation
• Authors: Zeyu Ren, Xiang Li, Yiran Wang, Zeyu Zhang, Hao Tang,
• Abstract summary: We propose StereoAdapter-2, which replaces the conventional ConvGRU updater with a novel ConvSS2D operator.<n>We construct UW-StereoDepth-80K, a large-scale synthetic underwater stereo dataset.<n>Our framework achieves state-of-the-art zero-shot performance on underwater benchmarks.
• Score: 18.410248448681514
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Stereo depth estimation is fundamental to underwater robotic perception, yet suffers from severe domain shifts caused by wavelength-dependent light attenuation, scattering, and refraction. Recent approaches leverage monocular foundation models with GRU-based iterative refinement for underwater adaptation; however, the sequential gating and local convolutional kernels in GRUs necessitate multiple iterations for long-range disparity propagation, limiting performance in large-disparity and textureless underwater regions. In this paper, we propose StereoAdapter-2, which replaces the conventional ConvGRU updater with a novel ConvSS2D operator based on selective state space models. The proposed operator employs a four-directional scanning strategy that naturally aligns with epipolar geometry while capturing vertical structural consistency, enabling efficient long-range spatial propagation within a single update step at linear computational complexity. Furthermore, we construct UW-StereoDepth-80K, a large-scale synthetic underwater stereo dataset featuring diverse baselines, attenuation coefficients, and scattering parameters through a two-stage generative pipeline combining semantic-aware style transfer and geometry-consistent novel view synthesis. Combined with dynamic LoRA adaptation inherited from StereoAdapter, our framework achieves state-of-the-art zero-shot performance on underwater benchmarks with 17% improvement on TartanAir-UW and 7.2% improvment on SQUID, with real-world validation on the BlueROV2 platform demonstrates the robustness of our approach. Code: https://github.com/AIGeeksGroup/StereoAdapter-2. Website: https://aigeeksgroup.github.io/StereoAdapter-2.

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