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With the development of underwater object grabbing technology, underwater object recognition and segmentation of high accuracy has become a challenge. The existing underwater object detection technology can only give the general position of…

Computer Vision and Pattern Recognition · Computer Science 2021-08-27 Zhiwei Ma , Haojie Li , Zhihui Wang , Dan Yu , Tianyi Wang , Yingshuang Gu , Xin Fan , Zhongxuan Luo

Instance segmentation plays a vital role in the morphological quantification of biomedical entities such as tissues and cells, enabling precise identification and delineation of different structures. Current methods often address the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Runsheng Liu , Hao Jiang , Yanning Zhou , Huangjing Lin , Liansheng Wang , Hao Chen

Obstacle detection by semantic segmentation shows a great promise for autonomous navigation in unmanned surface vehicles (USV). However, existing methods suffer from poor estimation of the water edge in the presence of visual ambiguities,…

Computer Vision and Pattern Recognition · Computer Science 2020-01-08 Borja Bovcon , Matej Kristan

Obstacle detection plays an important role in unmanned surface vehicles (USV). The USVs operate in highly diverse environments in which an obstacle may be a floating piece of wood, a scuba diver, a pier, or a part of a shoreline, which…

Computer Vision and Pattern Recognition · Computer Science 2015-03-09 Matej Kristan , Vildana Sulic , Stanislav Kovacic , Janez Pers

Most existing underwater instance segmentation approaches are constrained by close-vocabulary prediction, limiting their ability to recognize novel marine categories. To support evaluation, we introduce \textbf{MARIS} (\underline{Mar}ine…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Bingyu Li , Feiyu Wang , Da Zhang , Zhiyuan Zhao , Junyu Gao , Xuelong Li

Semi-Supervised Instance Segmentation (SSIS) aims to leverage an amount of unlabeled data during training. Previous frameworks primarily utilized the RGB information of unlabeled images to generate pseudo-labels. However, such a mechanism…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Xin Chen , Jie Hu , Xiawu Zheng , Jianghang Lin , Liujuan Cao , Rongrong Ji

3D scene understanding has become an essential area of research with applications in autonomous driving, robotics, and augmented reality. Recently, 3D Gaussian Splatting (3DGS) has emerged as a powerful approach, combining explicit modeling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Haijie Li , Yanmin Wu , Jiarui Meng , Qiankun Gao , Zhiyao Zhang , Ronggang Wang , Jian Zhang

Underwater scenes intrinsically involve degradation problems owing to heterogeneous ocean elements. Prevailing underwater image enhancement (UIE) methods stick to straightforward feature modeling to learn the mapping function, which leads…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Zhixiong Huang , Xinying Wang , Chengpei Xu , Jinjiang Li , Lin Feng

Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aquatic environments. This paper presents an enhanced Gaussian Splatting-based framework that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

Curating high quality datasets that play a key role in the emergence of new AI applications requires considerable time, money, and computational resources. So, effective ownership protection of datasets is becoming critical. Recently, to…

Multimedia · Computer Science 2024-07-19 Saeed Ranjbar Alvar , Mohammad Akbari , David Ming Xuan Yue , Yong Zhang

Weakly Supervised Semantic Segmentation (WSSS) is a challenging task aiming to learn the segmentation labels from class-level labels. In the literature, exploiting the information obtained from Class Activation Maps (CAMs) is widely used…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Cenk Bircanoglu , Nafiz Arica

Recently, 3D Gaussian Splatting has emerged as a prominent research direction owing to its ultrarapid training speed and high-fidelity rendering capabilities. However, the unstructured and irregular nature of Gaussian point clouds poses…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Xiao Ren , Yu Liu , Ning An , Jian Cheng , Xin Qiao , He Kong

Underwater simulators offer support for building robust underwater perception solutions. Significant work has recently been done to develop new simulators and to advance the performance of existing underwater simulators. Still, there…

Robotics · Computer Science 2025-08-12 Jingyu Song , Haoyu Ma , Onur Bagoren , Advaith V. Sethuraman , Yiting Zhang , Katherine A. Skinner

Being able to effectively identify clouds and monitor their evolution is one important step toward more accurate quantitative precipitation estimation and forecast. In this study, a new gradient-based cloud-image segmentation technique is…

Computer Vision and Pattern Recognition · Computer Science 2018-10-01 Negin Hayatbini , Kuo-lin Hsu , Soroosh Sorooshian , Yunji Zhang , Fuqing Zhang

In this paper, we present the first large-scale dataset for semantic Segmentation of Underwater IMagery (SUIM). It contains over 1500 images with pixel annotations for eight object categories: fish (vertebrates), reefs (invertebrates),…

Computer Vision and Pattern Recognition · Computer Science 2020-09-15 Md Jahidul Islam , Chelsey Edge , Yuyang Xiao , Peigen Luo , Muntaqim Mehtaz , Christopher Morse , Sadman Sakib Enan , Junaed Sattar

Salient instance segmentation is a new challenging task that received widespread attention in the saliency detection area. The new generation of saliency detection provides a strong theoretical and technical basis for video surveillance.…

Computer Vision and Pattern Recognition · Computer Science 2021-04-29 Jialun Pei , He Tang , Tianyang Cheng , Chuanbo Chen

We introduce SeaSplat, a method to enable real-time rendering of underwater scenes leveraging recent advances in 3D radiance fields. Underwater scenes are challenging visual environments, as rendering through a medium such as water…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Daniel Yang , John J. Leonard , Yogesh Girdhar

Image segmentation is a vital task for providing human assistance and enhancing autonomy in our daily lives. In particular, RGB-D segmentation-leveraging both visual and depth cues-has attracted increasing attention as it promises richer…

Computer Vision and Pattern Recognition · Computer Science 2025-01-06 Aecheon Jung , Soyun Choi , Junhong Min , Sungeun Hong

While 3D Gaussian Splatting enables high-quality real-time rendering, existing Gaussian-based frameworks for 3D semantic segmentation still face significant challenges in boundary recognition accuracy. To address this, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Zehao Li , Wenwei Han , Yujun Cai , Hao Jiang , Baolong Bi , Shuqin Gao , Honglong Zhao , Zhaoqi Wang

Novel view synthesis for underwater scene reconstruction presents unique challenges due to complex light-media interactions. Optical scattering and absorption in water body bring inhomogeneous medium attenuation interference that disrupts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Jieyu Yuan , Yujun Li , Yuanlin Zhang , Chunle Guo , Xiongxin Tang , Ruixing Wang , Chongyi Li