{ "id": 571312, "title": "🖼️🔮 3D Image Matching Challenge Resources 🔮🖼️", "url": "/competitions/image-matching-challenge-2025/discussion/571312", "author_name": "", "post_date": "2025-04-02T14:58:14.055050700Z", "votes": 20, "comment_count": 13, "views": 0, "content": "

🖼️🔮 3D Image Matching Challenge Resources 🔮🖼️

\n

Some content that could be used for this contest!

\n

Research Papers

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
PaperLinkNotebook
SPHORB: A Fast and Robust Binary Feature on the Sphere (IJCV 2015)PaperGitHub
PanoPoint: Self-Supervised Feature Points Detection and Description for 360° Panorama (CVPRW 2023)Paper-
SphereGlue: Learning Keypoint Matching on High Resolution Spherical Images (CVPRW 2023)PaperGitHub
Structure from motion using full spherical panoramic camerasPaper-
Robust 360-8PA: Redesigning The Normalized 8-point Algorithm for 360-FoV ImagesPaperGitHub
CoVisPose: Co-visibility Pose Transformer for Wide-Baseline Relative Pose Estimation in 360 Indoor Panoramas (ECCV 2022)Paper-
GPR-Net: Multi-view Layout Estimation via a Geometry-aware Panorama Registration Network (arXiv 2022)Paper-
Graph-CoVis: GNN-based Multi-view Panorama Global Pose Estimation (arXiv 2023)Paper-
\n

2023 Contest - Top Notebooks

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DescriptionURL
EDA IMC 3D Plots Interactive VisualizationKaggle
IMC 2023 Submission ExampleKaggle
IMC 2023 Submission Example (Alternative)Kaggle
Image Matching Data Discovery and SIFT FeaturesKaggle
IMC2023 From RepoKaggle
IMC2023 Final PublicationKaggle
Multi-Descriptors MAGSACKaggle
\n

2022 Contest - Top Notebooks

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DescriptionURL
IMC 2022 Kornia Score 0.725Kaggle
Image Matching Challenge 2022 EDAKaggle
IMC 2022 Kornia LoFTR From 0.533 to 0.721Kaggle
IMC2022 Training DataKaggle
Public Baseline DKM 0.667Kaggle
IMC 2022 Final EnsembleKaggle
LoFTR SuperGlue DKM With InspirationKaggle
IMC 2022 209410736Kaggle
Two-Stage LoFTR SuperGlue DKMKaggle
IMC2022 Ensemble With DKM ROIKaggle
\n

Other Good Resources

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DescriptionURL
Image Matching Challenge 2022 Baseline KorniaKaggle
Image Matching Challenge 2022Kaggle
IMC Understanding The BaselineKaggle
Quadtree Image Matching Challenge 2022Kaggle
Image Matching Challenge 2023 InferenceKaggle
IMC 2022 Kornia LoFTR Score Plateau 0.726Kaggle
Detector-Free Local Feature Matching with TransformerKaggle
\n

All the best to you!

", "messages": [ { "id": "3168554", "postDate": "04/02/2025 14:58:14", "content": "

🖼️🔮 3D Image Matching Challenge Resources 🔮🖼️

\n

Some content that could be used for this contest!

\n

Research Papers

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
PaperLinkNotebook
SPHORB: A Fast and Robust Binary Feature on the Sphere (IJCV 2015)PaperGitHub
PanoPoint: Self-Supervised Feature Points Detection and Description for 360° Panorama (CVPRW 2023)Paper-
SphereGlue: Learning Keypoint Matching on High Resolution Spherical Images (CVPRW 2023)PaperGitHub
Structure from motion using full spherical panoramic camerasPaper-
Robust 360-8PA: Redesigning The Normalized 8-point Algorithm for 360-FoV ImagesPaperGitHub
CoVisPose: Co-visibility Pose Transformer for Wide-Baseline Relative Pose Estimation in 360 Indoor Panoramas (ECCV 2022)Paper-
GPR-Net: Multi-view Layout Estimation via a Geometry-aware Panorama Registration Network (arXiv 2022)Paper-
Graph-CoVis: GNN-based Multi-view Panorama Global Pose Estimation (arXiv 2023)Paper-
\n

2023 Contest - Top Notebooks

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DescriptionURL
EDA IMC 3D Plots Interactive VisualizationKaggle
IMC 2023 Submission ExampleKaggle
IMC 2023 Submission Example (Alternative)Kaggle
Image Matching Data Discovery and SIFT FeaturesKaggle
IMC2023 From RepoKaggle
IMC2023 Final PublicationKaggle
Multi-Descriptors MAGSACKaggle
\n

2022 Contest - Top Notebooks

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DescriptionURL
IMC 2022 Kornia Score 0.725Kaggle
Image Matching Challenge 2022 EDAKaggle
IMC 2022 Kornia LoFTR From 0.533 to 0.721Kaggle
IMC2022 Training DataKaggle
Public Baseline DKM 0.667Kaggle
IMC 2022 Final EnsembleKaggle
LoFTR SuperGlue DKM With InspirationKaggle
IMC 2022 209410736Kaggle
Two-Stage LoFTR SuperGlue DKMKaggle
IMC2022 Ensemble With DKM ROIKaggle
\n

Other Good Resources

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DescriptionURL
Image Matching Challenge 2022 Baseline KorniaKaggle
Image Matching Challenge 2022Kaggle
IMC Understanding The BaselineKaggle
Quadtree Image Matching Challenge 2022Kaggle
Image Matching Challenge 2023 InferenceKaggle
IMC 2022 Kornia LoFTR Score Plateau 0.726Kaggle
Detector-Free Local Feature Matching with TransformerKaggle
\n

All the best to you!

", "rawMarkdown": "# 🖼️🔮 3D Image Matching Challenge Resources 🔮🖼️\n\n### ***Some content that could be used for this contest!***\n\n## Research Papers\n\n| Paper | Link | Notebook |\n|-------|------|----------|\n| SPHORB: A Fast and Robust Binary Feature on the Sphere (IJCV 2015) | [Paper](http://cic.tju.edu.cn/faculty/lwan/paper/SPHORB/SPHORB.html) | [GitHub](https://github.com/tdsuper/SPHORB) |\n| PanoPoint: Self-Supervised Feature Points Detection and Description for 360° Panorama (CVPRW 2023) | [Paper](https://openaccess.thecvf.com/content/CVPR2023W/OmniCV/papers/Zhang_PanoPoint_Self-Supervised_Feature_Points_Detection_and_Description_for_360deg_Panorama_CVPRW_2023_paper.pdf) | - |\n| SphereGlue: Learning Keypoint Matching on High Resolution Spherical Images (CVPRW 2023) | [Paper](https://openaccess.thecvf.com/content/CVPR2023W/IMW/papers/Gava_SphereGlue_Learning_Keypoint_Matching_on_High_Resolution_Spherical_Images_CVPRW_2023_paper.pdf) | [GitHub](https://github.com/vishalsharbidar/SphereGlue) |\n| Structure from motion using full spherical panoramic cameras | [Paper](http://av.dfki.de/~pagani/papers/Pagani2011_OMNIVIS.pdf) | - |\n| Robust 360-8PA: Redesigning The Normalized 8-point Algorithm for 360-FoV Images | [Paper](https://arxiv.org/pdf/2104.10900.pdf) | [GitHub](https://github.com/EnriqueSolarte/robust_360_8PA) |\n| CoVisPose: Co-visibility Pose Transformer for Wide-Baseline Relative Pose Estimation in 360 Indoor Panoramas (ECCV 2022) | [Paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136920610.pdf) | - |\n| GPR-Net: Multi-view Layout Estimation via a Geometry-aware Panorama Registration Network (arXiv 2022) | [Paper](https://arxiv.org/pdf/2210.11419.pdf) | - |\n| Graph-CoVis: GNN-based Multi-view Panorama Global Pose Estimation (arXiv 2023) | [Paper](https://arxiv.org/pdf/2304.13201.pdf) | - |\n\n## 2023 Contest - Top Notebooks\n\n| Description | URL |\n|-------------|-----|\n| EDA IMC 3D Plots Interactive Visualization | [Kaggle](https://www.kaggle.com/code/leonidkulyk/eda-imc-3d-plots-interactive-vis) |\n| IMC 2023 Submission Example | [Kaggle](https://www.kaggle.com/code/eduardtrulls/imc-2023-submission-example) |\n| IMC 2023 Submission Example (Alternative) | [Kaggle](https://www.kaggle.com/code/qi7axu/imc-2023-submission-example) |\n| Image Matching Data Discovery and SIFT Features | [Kaggle](https://www.kaggle.com/code/jessevanderlinden/image-matching-data-discovery-and-sift-features) |\n| IMC2023 From Repo | [Kaggle](https://www.kaggle.com/code/alexanderveicht/imc2023-from-repo) |\n| IMC2023 Final Publication | [Kaggle](https://www.kaggle.com/code/maxchen303/imc2023-final-pub) |\n| Multi-Descriptors MAGSAC | [Kaggle](https://www.kaggle.com/code/socratis/multi-descriptors-magsac) |\n\n## 2022 Contest - Top Notebooks\n\n| Description | URL |\n|-------------|-----|\n| IMC 2022 Kornia Score 0.725 | [Kaggle](https://www.kaggle.com/code/cbeaud/imc-2022-kornia-score-0-725) |\n| Image Matching Challenge 2022 EDA | [Kaggle](https://www.kaggle.com/code/dschettler8845/image-matching-challenge-2022-eda) |\n| IMC 2022 Kornia LoFTR From 0.533 to 0.721 | [Kaggle](https://www.kaggle.com/code/ammarali32/imc-2022-kornia-loftr-from-0-533-to-0-721) |\n| IMC2022 Training Data | [Kaggle](https://www.kaggle.com/code/eduardtrulls/imc2022-training-data) |\n| Public Baseline DKM 0.667 | [Kaggle](https://www.kaggle.com/code/radac98/public-baseline-dkm-0-667) |\n| IMC 2022 Final Ensemble | [Kaggle](https://www.kaggle.com/code/gufanmingmie/imc-2022-final-ensemble) |\n| LoFTR SuperGlue DKM With Inspiration | [Kaggle](https://www.kaggle.com/code/chankhavu/loftr-superglue-dkm-with-inspiration) |\n| IMC 2022 209410736 | [Kaggle](https://www.kaggle.com/code/will70917/imc-2022-209410736) |\n| Two-Stage LoFTR SuperGlue DKM | [Kaggle](https://www.kaggle.com/code/chankhavu/two-stage-loftr-superglue-dkm) |\n| IMC2022 Ensemble With DKM ROI | [Kaggle](https://www.kaggle.com/code/tmyok1984/imc2022-ensemble-with-dkm-roi) |\n\n## Other Good Resources\n\n| Description | URL |\n|-------------|-----|\n| Image Matching Challenge 2022 Baseline Kornia | [Kaggle](https://www.kaggle.com/code/ammarali32/image-matching-challenge-2022-baseline-kornia) |\n| Image Matching Challenge 2022 | [Kaggle](https://www.kaggle.com/code/cbeaud/image-matching-challenge-2022) |\n| IMC Understanding The Baseline | [Kaggle](https://www.kaggle.com/code/asarvazyan/imc-understanding-the-baseline) |\n| Quadtree Image Matching Challenge 2022 | [Kaggle](https://www.kaggle.com/code/dschettler8845/quadtree-image-matching-challenge-2022) |\n| Image Matching Challenge 2023 Inference | [Kaggle](https://www.kaggle.com/code/gunesevitan/image-matching-challenge-2023-inference) |\n| IMC 2022 Kornia LoFTR Score Plateau 0.726 | [Kaggle](https://www.kaggle.com/code/mcwema/imc-2022-kornia-loftr-score-plateau-0-726) |\n| Detector-Free Local Feature Matching with Transformer | [Kaggle](https://www.kaggle.com/code/remekkinas/detector-free-local-feature-matching-w-transformer) |\n\nAll the best to you!", "votes": null }, { "id": "3169436", "postDate": "04/03/2025 13:19:00", "content": "

Thanks for sharing its good for people who are bigginer to datascience field like me

", "rawMarkdown": "Thanks for sharing its good for people who are bigginer to datascience field like me", "votes": null }, { "id": "3172960", "postDate": "04/07/2025 11:15:04", "content": "

Thanks for the nice feedback and comments @harshitanarisetty . Appreciate it!

", "rawMarkdown": "Thanks for the nice feedback and comments @harshitanarisetty . Appreciate it!", "votes": null }, { "id": "3174143", "postDate": "04/08/2025 18:30:10", "content": "

I like what you have done here, I think it is a very good starting point for all image matching projects

", "rawMarkdown": "I like what you have done here, I think it is a very good starting point for all image matching projects", "votes": null }, { "id": "3174566", "postDate": "04/09/2025 08:20:26", "content": "

@orvile - Glad you liked them. Please share your recommendations as well!

", "rawMarkdown": "orvile - Glad you liked them. Please share your recommendations as well!", "votes": null }, { "id": "3174639", "postDate": "04/09/2025 09:38:00", "content": "

@kalilurrahman - Thank you for your comment, i have no additional suggestions or comment as i am new to this field of study. you have already written everything i think and they are all good and well organized

", "rawMarkdown": "kalilurrahman - Thank you for your comment, i have no additional suggestions or comment as i am new to this field of study. you have already written everything i think and they are all good and well organized", "votes": null }, { "id": "3176250", "postDate": "04/11/2025 06:12:55", "content": "

Thanks for sharing.

", "rawMarkdown": "Thanks for sharing.", "votes": null }, { "id": "3177975", "postDate": "04/13/2025 14:57:16", "content": "

Awesome work!

", "rawMarkdown": "Awesome work!", "votes": null }, { "id": "3189558", "postDate": "04/29/2025 11:37:07", "content": "

Thanks for sharing! Helps a lot!

", "rawMarkdown": "Thanks for sharing! Helps a lot!", "votes": null }, { "id": "3204030", "postDate": "05/17/2025 17:40:39", "content": "

Appreciate your effort! 🙌

", "rawMarkdown": "Appreciate your effort! 🙌", "votes": null }, { "id": "3204809", "postDate": "05/18/2025 21:15:28", "content": "

Hi\nHow many houers to learn and whith is most importent?

", "rawMarkdown": "Hi\nHow many houers to learn and whith is most importent?", "votes": null }, { "id": "3205388", "postDate": "05/19/2025 19:29:55", "content": "

it's completely perfect!

", "rawMarkdown": "it's completely perfect!", "votes": null }, { "id": "3246432", "postDate": "07/10/2025 23:51:07", "content": "
\n

This is really amazing to learn

\n
", "rawMarkdown": ">This is really amazing to learn", "votes": null }, { "id": "3255488", "postDate": "07/28/2025 18:54:36", "content": "

Thank you for sharing all of this!

", "rawMarkdown": "Thank you for sharing all of this!", "votes": null } ], "comments": [ { "id": 3169436, "author_name": "harshitanarisetty", "author_url": "", "post_date": "04/03/2025 13:19:00", "content": "

Thanks for sharing its good for people who are bigginer to datascience field like me

", "votes": null, "replies": [ { "id": 3172960, "author_name": "kalilurrahman", "author_url": "", "post_date": "04/07/2025 11:15:04", "content": "

Thanks for the nice feedback and comments @harshitanarisetty . Appreciate it!

", "votes": null, "replies": [] } ] }, { "id": 3174143, "author_name": "orvile", "author_url": "", "post_date": "04/08/2025 18:30:10", "content": "

I like what you have done here, I think it is a very good starting point for all image matching projects

", "votes": null, "replies": [ { "id": 3174566, "author_name": "kalilurrahman", "author_url": "", "post_date": "04/09/2025 08:20:26", "content": "

@orvile - Glad you liked them. Please share your recommendations as well!

", "votes": null, "replies": [ { "id": 3174639, "author_name": "orvile", "author_url": "", "post_date": "04/09/2025 09:38:00", "content": "

@kalilurrahman - Thank you for your comment, i have no additional suggestions or comment as i am new to this field of study. you have already written everything i think and they are all good and well organized

", "votes": null, "replies": [] } ] } ] }, { "id": 3176250, "author_name": "cudamax", "author_url": "", "post_date": "04/11/2025 06:12:55", "content": "

Thanks for sharing.

", "votes": null, "replies": [] }, { "id": 3177975, "author_name": "gurramgopichandh", "author_url": "", "post_date": "04/13/2025 14:57:16", "content": "

Awesome work!

", "votes": null, "replies": [] }, { "id": 3189558, "author_name": "borry1218", "author_url": "", "post_date": "04/29/2025 11:37:07", "content": "

Thanks for sharing! Helps a lot!

", "votes": null, "replies": [] }, { "id": 3204030, "author_name": "girishkalyan", "author_url": "", "post_date": "05/17/2025 17:40:39", "content": "

Appreciate your effort! 🙌

", "votes": null, "replies": [] }, { "id": 3204809, "author_name": "", "author_url": "", "post_date": "05/18/2025 21:15:28", "content": "

Hi\nHow many houers to learn and whith is most importent?

", "votes": null, "replies": [] }, { "id": 3205388, "author_name": "zahraalipour", "author_url": "", "post_date": "05/19/2025 19:29:55", "content": "

it's completely perfect!

", "votes": null, "replies": [] }, { "id": 3246432, "author_name": "tejalaveti2306", "author_url": "", "post_date": "07/10/2025 23:51:07", "content": "
\n

This is really amazing to learn

\n
", "votes": null, "replies": [] }, { "id": 3255488, "author_name": "abdelhakouanzougui2", "author_url": "", "post_date": "07/28/2025 18:54:36", "content": "

Thank you for sharing all of this!

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "3168554": "# 🖼️🔮 3D Image Matching Challenge Resources 🔮🖼️\n\n### ***Some content that could be used for this contest!***\n\n## Research Papers\n\n| Paper | Link | Notebook |\n|-------|------|----------|\n| SPHORB: A Fast and Robust Binary Feature on the Sphere (IJCV 2015) | [Paper](http://cic.tju.edu.cn/faculty/lwan/paper/SPHORB/SPHORB.html) | [GitHub](https://github.com/tdsuper/SPHORB) |\n| PanoPoint: Self-Supervised Feature Points Detection and Description for 360° Panorama (CVPRW 2023) | [Paper](https://openaccess.thecvf.com/content/CVPR2023W/OmniCV/papers/Zhang_PanoPoint_Self-Supervised_Feature_Points_Detection_and_Description_for_360deg_Panorama_CVPRW_2023_paper.pdf) | - |\n| SphereGlue: Learning Keypoint Matching on High Resolution Spherical Images (CVPRW 2023) | [Paper](https://openaccess.thecvf.com/content/CVPR2023W/IMW/papers/Gava_SphereGlue_Learning_Keypoint_Matching_on_High_Resolution_Spherical_Images_CVPRW_2023_paper.pdf) | [GitHub](https://github.com/vishalsharbidar/SphereGlue) |\n| Structure from motion using full spherical panoramic cameras | [Paper](http://av.dfki.de/~pagani/papers/Pagani2011_OMNIVIS.pdf) | - |\n| Robust 360-8PA: Redesigning The Normalized 8-point Algorithm for 360-FoV Images | [Paper](https://arxiv.org/pdf/2104.10900.pdf) | [GitHub](https://github.com/EnriqueSolarte/robust_360_8PA) |\n| CoVisPose: Co-visibility Pose Transformer for Wide-Baseline Relative Pose Estimation in 360 Indoor Panoramas (ECCV 2022) | [Paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136920610.pdf) | - |\n| GPR-Net: Multi-view Layout Estimation via a Geometry-aware Panorama Registration Network (arXiv 2022) | [Paper](https://arxiv.org/pdf/2210.11419.pdf) | - |\n| Graph-CoVis: GNN-based Multi-view Panorama Global Pose Estimation (arXiv 2023) | [Paper](https://arxiv.org/pdf/2304.13201.pdf) | - |\n\n## 2023 Contest - Top Notebooks\n\n| Description | URL |\n|-------------|-----|\n| EDA IMC 3D Plots Interactive Visualization | [Kaggle](https://www.kaggle.com/code/leonidkulyk/eda-imc-3d-plots-interactive-vis) |\n| IMC 2023 Submission Example | [Kaggle](https://www.kaggle.com/code/eduardtrulls/imc-2023-submission-example) |\n| IMC 2023 Submission Example (Alternative) | [Kaggle](https://www.kaggle.com/code/qi7axu/imc-2023-submission-example) |\n| Image Matching Data Discovery and SIFT Features | [Kaggle](https://www.kaggle.com/code/jessevanderlinden/image-matching-data-discovery-and-sift-features) |\n| IMC2023 From Repo | [Kaggle](https://www.kaggle.com/code/alexanderveicht/imc2023-from-repo) |\n| IMC2023 Final Publication | [Kaggle](https://www.kaggle.com/code/maxchen303/imc2023-final-pub) |\n| Multi-Descriptors MAGSAC | [Kaggle](https://www.kaggle.com/code/socratis/multi-descriptors-magsac) |\n\n## 2022 Contest - Top Notebooks\n\n| Description | URL |\n|-------------|-----|\n| IMC 2022 Kornia Score 0.725 | [Kaggle](https://www.kaggle.com/code/cbeaud/imc-2022-kornia-score-0-725) |\n| Image Matching Challenge 2022 EDA | [Kaggle](https://www.kaggle.com/code/dschettler8845/image-matching-challenge-2022-eda) |\n| IMC 2022 Kornia LoFTR From 0.533 to 0.721 | [Kaggle](https://www.kaggle.com/code/ammarali32/imc-2022-kornia-loftr-from-0-533-to-0-721) |\n| IMC2022 Training Data | [Kaggle](https://www.kaggle.com/code/eduardtrulls/imc2022-training-data) |\n| Public Baseline DKM 0.667 | [Kaggle](https://www.kaggle.com/code/radac98/public-baseline-dkm-0-667) |\n| IMC 2022 Final Ensemble | [Kaggle](https://www.kaggle.com/code/gufanmingmie/imc-2022-final-ensemble) |\n| LoFTR SuperGlue DKM With Inspiration | [Kaggle](https://www.kaggle.com/code/chankhavu/loftr-superglue-dkm-with-inspiration) |\n| IMC 2022 209410736 | [Kaggle](https://www.kaggle.com/code/will70917/imc-2022-209410736) |\n| Two-Stage LoFTR SuperGlue DKM | [Kaggle](https://www.kaggle.com/code/chankhavu/two-stage-loftr-superglue-dkm) |\n| IMC2022 Ensemble With DKM ROI | [Kaggle](https://www.kaggle.com/code/tmyok1984/imc2022-ensemble-with-dkm-roi) |\n\n## Other Good Resources\n\n| Description | URL |\n|-------------|-----|\n| Image Matching Challenge 2022 Baseline Kornia | [Kaggle](https://www.kaggle.com/code/ammarali32/image-matching-challenge-2022-baseline-kornia) |\n| Image Matching Challenge 2022 | [Kaggle](https://www.kaggle.com/code/cbeaud/image-matching-challenge-2022) |\n| IMC Understanding The Baseline | [Kaggle](https://www.kaggle.com/code/asarvazyan/imc-understanding-the-baseline) |\n| Quadtree Image Matching Challenge 2022 | [Kaggle](https://www.kaggle.com/code/dschettler8845/quadtree-image-matching-challenge-2022) |\n| Image Matching Challenge 2023 Inference | [Kaggle](https://www.kaggle.com/code/gunesevitan/image-matching-challenge-2023-inference) |\n| IMC 2022 Kornia LoFTR Score Plateau 0.726 | [Kaggle](https://www.kaggle.com/code/mcwema/imc-2022-kornia-loftr-score-plateau-0-726) |\n| Detector-Free Local Feature Matching with Transformer | [Kaggle](https://www.kaggle.com/code/remekkinas/detector-free-local-feature-matching-w-transformer) |\n\nAll the best to you!", "3169436": "Thanks for sharing its good for people who are bigginer to datascience field like me", "3172960": "Thanks for the nice feedback and comments @harshitanarisetty . Appreciate it!", "3174143": "I like what you have done here, I think it is a very good starting point for all image matching projects", "3174566": "orvile - Glad you liked them. Please share your recommendations as well!", "3174639": "kalilurrahman - Thank you for your comment, i have no additional suggestions or comment as i am new to this field of study. you have already written everything i think and they are all good and well organized", "3176250": "Thanks for sharing.", "3177975": "Awesome work!", "3189558": "Thanks for sharing! Helps a lot!", "3204030": "Appreciate your effort! 🙌", "3204809": "Hi\nHow many houers to learn and whith is most importent?", "3205388": "it's completely perfect!", "3246432": ">This is really amazing to learn", "3255488": "Thank you for sharing all of this!" }, "source": "meta" }