Survey on Advanced Visibility Restoration and Object Segmentation Techniques in Adverse Weather Conditions |
Author(s): |
| Saba Attar , Shivnagar Vidya Prasarak Mandals College Of Engineering Baramati; Samiksha More, Shivnagar Vidya Prasarak Mandals College Of Engineering Baramati; Snehal Bhujbal, Shivnagar Vidya Prasarak Mandals College Of Engineering Baramati; Prof. Y. R. Khalate, Shivnagar Vidya Prasarak Mandals College Of Engineering Baramati; Prof. J. H. Shaikh, Shivnagar Vidya Prasarak Mandals College Of Engineering Baramati |
Keywords: |
| Visibility Restoration, Optical Flow, Foggy Scenes, Semi-Supervised Learning, Video Object Segmentation, Adverse Weather, Deep Learning, Cyclic Mechanism |
Abstract |
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This paper provides a survey of three state-of-the-art techniques focusing on visibility restoration in diverse weather conditions, optical flow estimation in dense fog, and semi-supervised video object segmentation. The unified approach towards weather visibility restoration, the use of semi-supervised learning for optical flow in foggy environments, and the cyclic mechanism for video object segmentation are explored. These methods are compared in terms of system architecture, datasets, and performance metrics. Through this survey, we aim to provide insights into advancements in these domains, highlighting future trends and areas for improvement. |
Other Details |
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Paper ID: IJSRDV12I90025 Published in: Volume : 12, Issue : 9 Publication Date: 01/12/2024 Page(s): 45-49 |
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