Hi everyone,
\nWe are happy to announce our fifth annual challenge, focused on helping predict the presence of plant and animal species at locations using previous observations paired with aerial images and environmental features. The challenge is part of LifeCLEF 2021 lab at CLEF 2021 and of the Eighth Workshop on Fine-Grained Visual Categorization (FGVC8) at CVPR 2021.
\nIn our first challenges, GeoLifeCLEF 2017, GeoLifeCLEF 2018 and GeoLifeCLEF 2019, each observation was associated only with environmental features given as vectors or patches extracted around the observation. Each year, the number of observations and species to predict increased gradually. Last year, in GeoLifeCLEF 2020, aerial images were added to each observation, furthermore, the number of species to detect was drastically increased to cover 33K species using data from, both, Pl@ntNet and iNaturalist.
\nThis year's challenge is based on the same data than last year but in a more user-friendly and more memory efficient format. Moreover, we provide more starter code on our GitHub, such has data loading and visualization utilities and notebooks, to help participants enter the competition.
\nLooking forward to the interesting and creative solutions that you all come up with. Feel free to ask questions here, or on the GitHub page!
", "messages": [ { "id": "1249635", "postDate": "03/23/2021 12:23:33", "content": "Hi everyone,
\nWe are happy to announce our fifth annual challenge, focused on helping predict the presence of plant and animal species at locations using previous observations paired with aerial images and environmental features. The challenge is part of LifeCLEF 2021 lab at CLEF 2021 and of the Eighth Workshop on Fine-Grained Visual Categorization (FGVC8) at CVPR 2021.
\nIn our first challenges, GeoLifeCLEF 2017, GeoLifeCLEF 2018 and GeoLifeCLEF 2019, each observation was associated only with environmental features given as vectors or patches extracted around the observation. Each year, the number of observations and species to predict increased gradually. Last year, in GeoLifeCLEF 2020, aerial images were added to each observation, furthermore, the number of species to detect was drastically increased to cover 33K species using data from, both, Pl@ntNet and iNaturalist.
\nThis year's challenge is based on the same data than last year but in a more user-friendly and more memory efficient format. Moreover, we provide more starter code on our GitHub, such has data loading and visualization utilities and notebooks, to help participants enter the competition.
\nLooking forward to the interesting and creative solutions that you all come up with. Feel free to ask questions here, or on the GitHub page!
", "rawMarkdown": "Hi everyone,\n\nWe are happy to announce our fifth annual challenge, focused on helping predict the presence of plant and animal species at locations using previous observations paired with aerial images and environmental features. The challenge is part of [LifeCLEF 2021 lab](https://www.imageclef.org/LifeCLEF2021) at [CLEF 2021](http://clef2021.clef-initiative.eu/) and of the [Eighth Workshop on Fine-Grained Visual Categorization (FGVC8)](https://sites.google.com/view/fgvc8) at [CVPR 2021](http://cvpr2021.thecvf.com/).\n\nIn our first challenges, [GeoLifeCLEF 2017](https://www.imageclef.org/lifeclef/2017/GeoLifeCLEF), [GeoLifeCLEF 2018](https://www.imageclef.org/node/229) and [GeoLifeCLEF 2019](https://www.imageclef.org/GeoLifeCLEF2019), each observation was associated only with environmental features given as vectors or patches extracted around the observation. Each year, the number of observations and species to predict increased gradually. Last year, in [GeoLifeCLEF 2020](https://www.imageclef.org/GeoLifeCLEF2020), aerial images were added to each observation, furthermore, the number of species to detect was drastically increased to cover 33K species using data from, both, Pl@ntNet and iNaturalist.\n\nThis year's challenge is based on the same data than last year but in a more user-friendly and more memory efficient format. Moreover, we provide more starter code on our [GitHub](https://github.com/maximiliense/GLC), such has data loading and visualization utilities and notebooks, to help participants enter the competition.\n\nLooking forward to the interesting and creative solutions that you all come up with. Feel free to ask questions here, or on the [GitHub](https://github.com/maximiliense/GLC) page!", "votes": null }, { "id": "1269737", "postDate": "04/10/2021 21:17:26", "content": "Hi, thanks for organizing this competition. I wonder if top participants on this competition will also receive chance to present at CVPR 2021 workshop, just like other competitions of FGVC8?
", "rawMarkdown": "Hi, thanks for organizing this competition. I wonder if top participants on this competition will also receive chance to present at CVPR 2021 workshop, just like other competitions of FGVC8?", "votes": null }, { "id": "1270317", "postDate": "04/11/2021 14:21:45", "content": "Hi! Yes, this is also the case for this competition. More details on this aspect is given in the \"Context\" section of the Overview page.
", "rawMarkdown": "Hi! Yes, this is also the case for this competition. More details on this aspect is given in the \"Context\" section of the [Overview page](https://www.kaggle.com/c/geolifeclef-2021/overview).", "votes": null }, { "id": "1271705", "postDate": "04/12/2021 19:52:38", "content": "Thank you! I should've read the overview more thoroughly, seems like I've missed that part when I was skimming it.
", "rawMarkdown": "Thank you! I should've read the overview more thoroughly, seems like I've missed that part when I was skimming it.", "votes": null } ], "comments": [ { "id": 1269737, "author_name": "jiny333", "author_url": "", "post_date": "04/10/2021 21:17:26", "content": "Hi, thanks for organizing this competition. I wonder if top participants on this competition will also receive chance to present at CVPR 2021 workshop, just like other competitions of FGVC8?
", "votes": null, "replies": [ { "id": 1270317, "author_name": "tlorieul", "author_url": "", "post_date": "04/11/2021 14:21:45", "content": "Hi! Yes, this is also the case for this competition. More details on this aspect is given in the \"Context\" section of the Overview page.
", "votes": null, "replies": [] }, { "id": 1271705, "author_name": "jiny333", "author_url": "", "post_date": "04/12/2021 19:52:38", "content": "Thank you! I should've read the overview more thoroughly, seems like I've missed that part when I was skimming it.
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "1249635": "Hi everyone,\n\nWe are happy to announce our fifth annual challenge, focused on helping predict the presence of plant and animal species at locations using previous observations paired with aerial images and environmental features. The challenge is part of [LifeCLEF 2021 lab](https://www.imageclef.org/LifeCLEF2021) at [CLEF 2021](http://clef2021.clef-initiative.eu/) and of the [Eighth Workshop on Fine-Grained Visual Categorization (FGVC8)](https://sites.google.com/view/fgvc8) at [CVPR 2021](http://cvpr2021.thecvf.com/).\n\nIn our first challenges, [GeoLifeCLEF 2017](https://www.imageclef.org/lifeclef/2017/GeoLifeCLEF), [GeoLifeCLEF 2018](https://www.imageclef.org/node/229) and [GeoLifeCLEF 2019](https://www.imageclef.org/GeoLifeCLEF2019), each observation was associated only with environmental features given as vectors or patches extracted around the observation. Each year, the number of observations and species to predict increased gradually. Last year, in [GeoLifeCLEF 2020](https://www.imageclef.org/GeoLifeCLEF2020), aerial images were added to each observation, furthermore, the number of species to detect was drastically increased to cover 33K species using data from, both, Pl@ntNet and iNaturalist.\n\nThis year's challenge is based on the same data than last year but in a more user-friendly and more memory efficient format. Moreover, we provide more starter code on our [GitHub](https://github.com/maximiliense/GLC), such has data loading and visualization utilities and notebooks, to help participants enter the competition.\n\nLooking forward to the interesting and creative solutions that you all come up with. Feel free to ask questions here, or on the [GitHub](https://github.com/maximiliense/GLC) page!", "1269737": "Hi, thanks for organizing this competition. I wonder if top participants on this competition will also receive chance to present at CVPR 2021 workshop, just like other competitions of FGVC8?", "1270317": "Hi! Yes, this is also the case for this competition. More details on this aspect is given in the \"Context\" section of the [Overview page](https://www.kaggle.com/c/geolifeclef-2021/overview).", "1271705": "Thank you! I should've read the overview more thoroughly, seems like I've missed that part when I was skimming it." }, "source": "meta" }