arXiv Computer Vision By Alexander Ingold, Sabina D. Menon, Aadhi Umamageswaran, Alec Ikei, May H. Hlaing, Syed N. Qadri, Rajesh Menon

Computational imaging through turbid, bubbly and flowing water near the telescope

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arXiv AI
Oct 9

Continuous Ground-Truth Construction and a Recovery Policy for Air--Water Robotic Tracking

The paper presents a pipeline for constructing accurate ground‑truth annotations for visual tracking across the air–water interface, synchronizing camera frames with motion‑capture data and correcting underwater projections. It introduces a Cross‑Medium Recovery Policy (CMRP) that uses confidence‑triggered template selection to improve MixFormerV2’s tracking performance without retraining the backbone. CMRP raises Macro Success AUC by 2.95 points and increases tracking coverage while reducing recovery latency.

By Jiangong Xiao, Zhe Sun, Kanzhong Yao, Yuanbo Bi, Haofei Zhao, Ruixuan Hu, Guan Huang, Xuelong Li
arXiv Computer Vision
Oct 12

CoRef-DETR: Decoupled Global Context and Selective Boundary-Category Refinement for Underwater Instance Segmentation

CoRef-DETR is a compact detection transformer designed for underwater instance segmentation, addressing errors from context, boundaries, and categories. It uses a decoupled global context detector with 33.4 M parameters, a lightweight boundary refiner of 47.7 k parameters, and a crop‑probe category branch that revises up to three mask categories per image. The method achieves state‑of‑the‑art mask AP on multiple UIIS datasets and runs in 26–37 ms on an NVIDIA T4 GPU, outperforming larger models.

By M. Fazri Nizar, Julian Supardi, Muhammad Naufal Rachmatullah