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Recent works have shown that combining object detection and tracking tasks, in the case of video data, results in higher performance for both tasks, but they require a high frame-rate as a strict requirement for performance. This is…

计算机视觉与模式识别 · 计算机科学 2020-05-26 Bharti Munjal , Abdul Rafey Aftab , Sikandar Amin , Meltem D. Brandlmaier , Federico Tombari , Fabio Galasso

Existing datasets for RGB-DVS tracking are collected with DVS346 camera and their resolution ($346 \times 260$) is low for practical applications. Actually, only visible cameras are deployed in many practical systems, and the newly designed…

计算机视觉与模式识别 · 计算机科学 2024-01-08 Yabin Zhu , Xiao Wang , Chenglong Li , Bo Jiang , Lin Zhu , Zhixiang Huang , Yonghong Tian , Jin Tang

This paper introduces a novel approach to video object detection detection and tracking on Unmanned Aerial Vehicles (UAVs). By incorporating metadata, the proposed approach creates a memory map of object locations in actual world…

计算机视觉与模式识别 · 计算机科学 2023-03-08 Benjamin Kiefer , Yitong Quan , Andreas Zell

The SportsMOT dataset aims to solve multiple object tracking of athletes in different sports scenes such as basketball or soccer. The dataset is challenging because of the unstable camera view, athletes' complex trajectory, and complicated…

计算机视觉与模式识别 · 计算机科学 2023-02-16 Jie Wang , Yuzhou Peng , Xiaodong Yang , Ting Wang , Yanming Zhang

Underwater caves are challenging environments that are crucial for water resource management, and for our understanding of hydro-geology and history. Mapping underwater caves is a time-consuming, labor-intensive, and hazardous operation.…

图像与视频处理 · 电气工程与系统科学 2023-06-29 Boxiao Yu , Reagan Tibbetts , Titon Barua , Ailani Morales , Ioannis Rekleitis , Md Jahidul Islam

Many underwater applications, such as offshore asset inspections, rely on visual inspection and detailed 3D reconstruction. Recent advancements in underwater visual SLAM systems for aquatic environments have garnered significant attention…

机器人学 · 计算机科学 2025-06-06 Yifan Peng , Yuze Hong , Ziyang Hong , Apple Pui-Yi Chui , Junfeng Wu

Small Multi-Object Tracking (SMOT) is particularly challenging when targets occupy only a few dozen pixels, rendering detection and appearance-based association unreliable. Building on the success of the MVA2023 SOD4SB challenge, this paper…

This paper addresses the challenging problem of image enhancement in complex underwater scenes by proposing a solution based on deep learning. The proposed method skillfully integrates two deep convolutional neural network models, VGG19 and…

计算机视觉与模式识别 · 计算机科学 2025-08-27 Aoqi Li , Yanghui Song , Jichao Dao , Chengfu Yang

Deep learning-based underwater object detection (UOD) remains a major challenge due to the degraded visibility and difficulty to obtain sufficient underwater object images captured from various perspectives for training. To address these…

计算机视觉与模式识别 · 计算机科学 2022-03-10 Xiuyuan Li , Fengchao Li , Jiangang Yu , Guowen An

Relying on Transformer for complex visual feature learning, object tracking has witnessed the new standard for state-of-the-arts (SOTAs). However, this advancement accompanies by larger training data and longer training period, making…

计算机视觉与模式识别 · 计算机科学 2022-07-05 Mingzhe Guo , Zhipeng Zhang , Heng Fan , Liping Jing

In recent years, significant progress has been made in the field of underwater image enhancement (UIE). However, its practical utility for high-level vision tasks, such as underwater object detection (UOD) in Autonomous Underwater Vehicles…

计算机视觉与模式识别 · 计算机科学 2024-03-29 Junjie Wen , Jinqiang Cui , Benyun Zhao , Bingxin Han , Xuchen Liu , Zhi Gao , Ben M. Chen

Underwater image restoration has been a challenging problem for decades since the advent of underwater photography. Most solutions focus on shallow water scenarios, where the scene is uniformly illuminated by the sunlight. However, the vast…

计算机视觉与模式识别 · 计算机科学 2024-04-26 Yifan Song , Mengkun She , Kevin Köser

Nowadays underwater vision systems are being widely applied in ocean research. However, the largest portion of the ocean - the deep sea - still remains mostly unexplored. Only relatively few image sets have been taken from the deep sea due…

计算机视觉与模式识别 · 计算机科学 2021-02-24 Yifan Song , David Nakath , Mengkun She , Furkan Elibol , Kevin Köser

Successful applications of complex vision-based behaviours underwater have lagged behind progress in terrestrial and aerial domains. This is largely due to the degraded image quality resulting from the physical phenomena involved in…

计算机视觉与模式识别 · 计算机科学 2023-03-08 Stewart Jamieson , Jonathan P. How , Yogesh Girdhar

Maritime environments often present hazardous situations due to factors such as moving ships or buoys, which become obstacles under the influence of waves. In such challenging conditions, the ability to detect and track potentially…

机器人学 · 计算机科学 2024-12-20 Jiwon Choi , Dongjin Cho , Gihyeon Lee , Hogyun Kim , Geonmo Yang , Joowan Kim , Younggun Cho

Underwater target tracking technology plays a pivotal role in marine resource exploration, environmental monitoring, and national defense security. Given that acoustic waves represent an effective medium for long-distance transmission in…

Unmanned surface vehicles can encounter a number of varied visual circumstances during operation, some of which can be very difficult to interpret. While most cases can be solved only using color camera images, some weather and lighting…

计算机视觉与模式识别 · 计算机科学 2025-12-22 Jon Muhovič , Janez Perš

Visual localization plays an important role in the positioning and navigation of robotics systems within previously visited environments. When visits occur over long periods of time, changes in the environment related to seasons or…

Multi-object tracking (MOT) in UAV-based video is challenging due to variations in viewpoint, low resolution, and the presence of small objects. While other research on MOT dedicated to aerial videos primarily focuses on the academic aspect…

计算机视觉与模式识别 · 计算机科学 2025-02-07 Nhat-Tan Do , Nhi Ngoc-Yen Nguyen , Dieu-Phuong Nguyen , Trong-Hop Do

Dynamic environments such as urban areas are still challenging for popular visual-inertial odometry (VIO) algorithms. Existing datasets typically fail to capture the dynamic nature of these environments, therefore making it difficult to…

机器人学 · 计算机科学 2021-02-12 Koji Minoda , Fabian Schilling , Valentin Wüest , Dario Floreano , Takehisa Yairi