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Related papers: synth-dacl: Does Synthetic Defect Data Enhance Seg…

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Finding and properly segmenting cracks in images of concrete is a challenging task. Cracks are thin and rough and being air filled do yield a very weak contrast in 3D images obtained by computed tomography. Enhancing and segmenting dark…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Tin Barisin , Christian Jung , Anna Nowacka , Claudia Redenbach , Katja Schladitz

We have developed an adaptive structural Deep Belief Network (Adaptive DBN) that finds an optimal network structure in a self-organizing manner during learning. The Adaptive DBN is the hierarchical architecture where each layer employs…

Computer Vision and Pattern Recognition · Computer Science 2021-10-26 Shin Kamada , Takumi Ichimura , Takashi Iwasaki

The generative AI technology offers an increasing variety of tools for generating entirely synthetic images that are increasingly indistinguishable from real ones. Unlike methods that alter portions of an image, the creation of completely…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Manos Schinas , Symeon Papadopoulos

Fracture is one of the main failure modes of engineering structures such as buildings and roads. Effective detection of surface cracks is significant for damage evaluation and structure maintenance. In recent years, the emergence and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Yu Zhang , Lin Zhang

Due to cyclic loading and fatigue stress cracks are generated, which affect the safety of any civil infrastructure. Nowadays machine vision is being used to assist us for appropriate maintenance, monitoring and inspection of concrete…

Computer Vision and Pattern Recognition · Computer Science 2020-09-23 Babloo Kumar , Sayantari Ghosh

The use of synthetic data in machine learning saves a significant amount of time when implementing an effective object detector. However, there is limited research in this domain. This study aims to improve upon previously applied…

Robotics · Computer Science 2024-02-13 Henry Gann , Josiah Bull , Trevor Gee , Mahla Nejati

Nighttime camera-based depth estimation is a highly challenging task, especially for autonomous driving applications, where accurate depth perception is essential for ensuring safe navigation. Models trained on daytime data often fail in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Simon de Moreau , Yasser Almehio , Andrei Bursuc , Hafid El-Idrissi , Bogdan Stanciulescu , Fabien Moutarde

Industrial defect detection is vital for upholding product quality across contemporary manufacturing systems. As the expectations for precision, automation, and scalability intensify, conventional inspection approaches are increasingly…

Computer Vision and Pattern Recognition · Computer Science 2025-07-21 Yuqi Cheng , Yunkang Cao , Haiming Yao , Wei Luo , Cheng Jiang , Hui Zhang , Weiming Shen

Transparent objects are common in daily life, and understanding their multi-layer depth information -- perceiving both the transparent surface and the objects behind it -- is crucial for real-world applications that interact with…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Hongyu Wen , Yiming Zuo , Venkat Subramanian , Patrick Chen , Jia Deng

The impact of snowfall on 3D object detection performance remains underexplored. Conducting such an evaluation requires a dataset with sufficient labelled data from both weather conditions, ideally captured in the same driving environment.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Mei Qi Tang , Sean Sedwards , Chengjie Huang , Krzysztof Czarnecki

Hard coatings play a critical role in industry, with ceramic materials offering outstanding hardness and thermal stability for applications that demand superior mechanical performance. However, deploying artificial intelligence (AI) for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Binwei Chen , Huachao Leng , Chi Yeung Mang , Tsz Wai Cheung , Yanhua Chen , Wai Keung Anthony Loh , Chi Ho Wong , Chak Yin Tang

Large-scale and categorical-balanced text data is essential for training effective Scene Text Recognition (STR) models, which is hard to achieve when collecting real data. Synthetic data offers a cost-effective and perfectly labeled…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Xingsong Ye , Yongkun Du , JiaXin Zhang , Chen Li , Jing Lyu , Zhineng Chen

Supervised training of an automated medical image analysis system often requires a large amount of expert annotations that are hard to collect. Moreover, the proportions of data available across different classes may be highly imbalanced…

Computer Vision and Pattern Recognition · Computer Science 2019-12-10 Yuan Xue , Jiarong Ye , Rodney Long , Sameer Antani , Zhiyun Xue , Xiaolei Huang

Conveyor belts are important equipment in modern industry, widely applied in production and manufacturing. Their health is much critical to operational efficiency and safety. Cracks are a major threat to belt health. Currently, considering…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Jianghong Huang , Luping Ji , Xin Ma , Mao Ye

Bridges are an essential part of the transportation infrastructure and need to be monitored periodically. Visual inspections by dedicated teams have been one of the primary tools in structural health monitoring (SHM) of bridge structures.…

Computer Vision and Pattern Recognition · Computer Science 2019-05-24 Seyed Omid Sajedi , Xiao Liang

Defect inspection is paramount within the closed-loop manufacturing system. However, existing datasets for defect inspection often lack precision and semantic granularity required for practical applications. In this paper, we introduce the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Shuai Yang , Zhifei Chen , Pengguang Chen , Xi Fang , Yixun Liang , Shu Liu , Yingcong Chen

The appearance of surface impurities (e.g., water stains, fingerprints, stickers) is an often-mentioned issue that causes degradation of automated visual inspection systems. At the same time, synthetic data generation techniques for visual…

Computer Vision and Pattern Recognition · Computer Science 2025-01-17 Runzhou Mao , Juraj Fulir , Christoph Garth , Petra Gospodnetić

The threat to safety of aging bridges has been recognized as a critical concern to the general public due to the poor condition of many bridges in the U.S. Currently, the bridge inspection is conducted manually, and it is not efficient to…

Robotics · Computer Science 2017-04-26 Hung M. La , Nenad Gucunski , Kristin Dana , Seong-Hoon Kee

The unsupervised visual inspection of defects in industrial products poses a significant challenge due to substantial variations in product surfaces. Current unsupervised models struggle to strike a balance between detecting texture and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Peng Wang , Haiming Yao , Wenyong Yu

We describe a method for unpaired realistic depth synthesis that learns diverse variations from the real-world depth scans and ensures geometric consistency between the synthetic and synthesized depth. The synthesized realistic depth can…

Computer Vision and Pattern Recognition · Computer Science 2023-08-16 Yuefan Shen , Yanchao Yang , Youyi Zheng , C. Karen Liu , Leonidas Guibas
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