Hi everyone,
\nWe are happy to announce our third annual herbarium fine-grained recognition challenge, in partnership with the New York Botanical Garden as part of their efforts to automate species recognition and aid with species discovery. The challenge is part of the Eighth Workshop on Fine-Grained Visual Categorization (FGVC8) at CVPR 2021.
\nOur first challenge, Herbarium 2019, focused on a dataset of ~46k flowering plants (Melastomes). In Herbarium 2020, the dataset was increased over 1M vascular land plants of the Americas.
\nThis year we have expanded the dataset to more than 2.5M images representing nearly 65,000 species from the Americas and Oceania that have been aligned to a standardized plant list (LCVP v1.0.2). To make things even more interesting, images are provided by five different institutions: the New York Botanical Garden (NY), Bishop Museum (BPBM), Naturalis Biodiversity Center (NL), Queensland Herbarium (BRI), and Auckland War Memorial Museum (AK). This leads to more intra-class variability to account for given how each institution presents herbarium specimens.
\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": 1234490, "postDate": "2021-03-11T09:47:58.903Z", "content": "Hi everyone,
\nWe are happy to announce our third annual herbarium fine-grained recognition challenge, in partnership with the New York Botanical Garden as part of their efforts to automate species recognition and aid with species discovery. The challenge is part of the Eighth Workshop on Fine-Grained Visual Categorization (FGVC8) at CVPR 2021.
\nOur first challenge, Herbarium 2019, focused on a dataset of ~46k flowering plants (Melastomes). In Herbarium 2020, the dataset was increased over 1M vascular land plants of the Americas.
\nThis year we have expanded the dataset to more than 2.5M images representing nearly 65,000 species from the Americas and Oceania that have been aligned to a standardized plant list (LCVP v1.0.2). To make things even more interesting, images are provided by five different institutions: the New York Botanical Garden (NY), Bishop Museum (BPBM), Naturalis Biodiversity Center (NL), Queensland Herbarium (BRI), and Auckland War Memorial Museum (AK). This leads to more intra-class variability to account for given how each institution presents herbarium specimens.
\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 third annual herbarium fine-grained recognition challenge, in partnership with the [New York Botanical Garden ](https://www.nybg.org/) as part of their efforts to automate species recognition and aid with species discovery. The challenge is part of the [Eighth Workshop on Fine-Grained Visual Categorization (FGVC8)](https://sites.google.com/view/fgvc8/home?authuser=0) at [CVPR 2021](http://cvpr2021.thecvf.com/).\n\nOur first challenge, [Herbarium 2019](https://www.kaggle.com/c/herbarium-2019-fgvc6), focused on a dataset of ~46k flowering plants (Melastomes). In [Herbarium 2020](https://www.kaggle.com/c/herbarium-2020-fgvc7), the dataset was increased over 1M vascular land plants of the Americas.\n\nThis year we have expanded the dataset to more than **2.5M images** representing nearly **65,000 species** from the Americas and Oceania that have been aligned to a standardized plant list ([LCVP v1.0.2](https://www.nature.com/articles/s41597-020-00702-z)). To make things even more interesting, images are provided by five different institutions: the [New York Botanical Garden](https://www.nybg.org/) (NY), [Bishop Museum](https://www.bishopmuseum.org/) (BPBM), [Naturalis Biodiversity Center](https://www.naturalis.nl/en) (NL), [Queensland Herbarium](https://www.qld.gov.au/environment/plants-animals/plants/herbarium) (BRI), and [Auckland War Memorial Museum](https://www.aucklandmuseum.com/) (AK). This leads to more intra-class variability to account for given how each institution presents herbarium specimens.\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 page](https://github.com/visipedia/herbarium_comp)!", "votes": 5 } ], "comments": [], "raw_markdown_by_id": { "1234490": "Hi everyone,\n\nWe are happy to announce our third annual herbarium fine-grained recognition challenge, in partnership with the [New York Botanical Garden ](https://www.nybg.org/) as part of their efforts to automate species recognition and aid with species discovery. The challenge is part of the [Eighth Workshop on Fine-Grained Visual Categorization (FGVC8)](https://sites.google.com/view/fgvc8/home?authuser=0) at [CVPR 2021](http://cvpr2021.thecvf.com/).\n\nOur first challenge, [Herbarium 2019](https://www.kaggle.com/c/herbarium-2019-fgvc6), focused on a dataset of ~46k flowering plants (Melastomes). In [Herbarium 2020](https://www.kaggle.com/c/herbarium-2020-fgvc7), the dataset was increased over 1M vascular land plants of the Americas.\n\nThis year we have expanded the dataset to more than **2.5M images** representing nearly **65,000 species** from the Americas and Oceania that have been aligned to a standardized plant list ([LCVP v1.0.2](https://www.nature.com/articles/s41597-020-00702-z)). To make things even more interesting, images are provided by five different institutions: the [New York Botanical Garden](https://www.nybg.org/) (NY), [Bishop Museum](https://www.bishopmuseum.org/) (BPBM), [Naturalis Biodiversity Center](https://www.naturalis.nl/en) (NL), [Queensland Herbarium](https://www.qld.gov.au/environment/plants-animals/plants/herbarium) (BRI), and [Auckland War Memorial Museum](https://www.aucklandmuseum.com/) (AK). This leads to more intra-class variability to account for given how each institution presents herbarium specimens.\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 page](https://github.com/visipedia/herbarium_comp)!" } }