IMC 2024 Methods & Solutions Review
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913416034123776 |
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| author | Gupta, Shyam Sharma, Dhanisha Huang, Songling |
| author_facet | Gupta, Shyam Sharma, Dhanisha Huang, Songling |
| contents | For the past three years, Kaggle has been hosting the Image Matching Challenge, which focuses on solving a 3D image reconstruction problem using a collection of 2D images. Each year, this competition fosters the development of innovative and effective methodologies by its participants. In this paper, we introduce an advanced ensemble technique that we developed, achieving a score of 0.153449 on the private leaderboard and securing the 160th position out of over 1,000 participants. Additionally, we conduct a comprehensive review of existing methods and techniques employed by top-performing teams in the competition. Our solution, alongside the insights gathered from other leading approaches, contributes to the ongoing advancement in the field of 3D image reconstruction. This research provides valuable knowledge for future participants and researchers aiming to excel in similar image matching and reconstruction challenges. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_03172 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | IMC 2024 Methods & Solutions Review Gupta, Shyam Sharma, Dhanisha Huang, Songling Computer Vision and Pattern Recognition Artificial Intelligence Applications For the past three years, Kaggle has been hosting the Image Matching Challenge, which focuses on solving a 3D image reconstruction problem using a collection of 2D images. Each year, this competition fosters the development of innovative and effective methodologies by its participants. In this paper, we introduce an advanced ensemble technique that we developed, achieving a score of 0.153449 on the private leaderboard and securing the 160th position out of over 1,000 participants. Additionally, we conduct a comprehensive review of existing methods and techniques employed by top-performing teams in the competition. Our solution, alongside the insights gathered from other leading approaches, contributes to the ongoing advancement in the field of 3D image reconstruction. This research provides valuable knowledge for future participants and researchers aiming to excel in similar image matching and reconstruction challenges. |
| title | IMC 2024 Methods & Solutions Review |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Applications |
| url | https://arxiv.org/abs/2407.03172 |