{
  "id": 137442,
  "title": "CALL FOR PAPERS: 7th Annual Workshop on Fine-Grained Visual Categorization at CVPR 2020",
  "url": "/competitions/herbarium-2020-fgvc7/discussion/137442",
  "author_name": "Kiat Chuan Tan",
  "post_date": "2020-03-20T18:46:05.456000",
  "votes": 1,
  "comment_count": 0,
  "views": 0,
  "content": "<p><strong>OVERVIEW</strong>\nFGVC7: The Seventh Workshop on Fine-Grained Visual Categorization\nJune 19th in conjunction with CVPR 2020, June, Seattle, USA.\nWebsite: <a href=\"https://sites.google.com/view/fgvc7\">https://sites.google.com/view/fgvc7</a>\nTwitter: @fgvcworkshop</p>\n\n<p>The purpose of this workshop is to bring together researchers to explore visual recognition across the continuum between basic level categorization (object recognition) and identification of individuals (face recognition, biometrics) within a category population. Participants are encouraged to submit short papers relevant to the workshop and to take part in a set of competitions organized in conjunction with the workshop - details below.</p>\n\n<p><strong>WORKSHOP DESCRIPTION</strong>\nFine-grained categorization (called `subordinate categorization’ in the psychology literature) lies in the continuum between basic-level categorization (object recognition) and the identification of individuals (e.g., face recognition, biometrics). The visual distinctions between similar categories are often quite subtle and therefore difficult to address with today’s general-purpose object recognition machinery. This is especially true for domains where data is not readily available on the web (e.g., medical images, or depth data), or domains for which training data is limited. It is likely that a radical re-thinking of the techniques used for representation learning, architecture design, human-in-the-loop learning, few-shot, and self-supervised learning that are currently used for visual recognition will be needed to improve fine-grained categorization.</p>\n\n<p>It is our hope that the invited talks, including researchers from scientific application domains, will shed light on human expertise and human performance in subordinate categorization and on motivating research applications. More information about previous FGVC workshops and competitions can be found at <a href=\"http://www.fgvc.org/\">http://www.fgvc.org/</a>.</p>\n\n<p><strong>PAPER SUBMISSION</strong>\nWe invite submission of 3 page (excluding references) extended abstracts (using the <a href=\"http://cvpr2020.thecvf.com/submission/main-conference/author-guidelines#submission-guidelines\">CVPR 2020</a> format) describing work in the domains suggested above or in closely-related areas. Accepted submissions will be presented as posters at the workshop. Reviewing of abstract submissions will be double-blind. The purpose of this workshop is not as a venue for publication, so much as a place to gather together those in the community working on or interested in FGVC. Submissions of work which has been previously published, including papers accepted to the main CVPR 2020 conference are allowed.</p>\n\n<p>For more details see - <a href=\"https://sites.google.com/view/fgvc7/submission\">https://sites.google.com/view/fgvc7/submission</a></p>\n\n<p>Topics of interest include the following:</p>\n\n<p>Fine-grained categorization\n* Novel datasets and data collection strategies for fine-grained categorization\n* Appropriate error metrics for fine-grained categorization\n* Low/few shot learning\n* Self-supervised learning\n* Transfer-learning from known to novel subcategories\n* Attribute and part based approaches\n* Taxonomic predictions</p>\n\n<p>Human-in-the-loop\n* Fine-grained categorization with humans in the loop\n* Embedding human experts’ knowledge into computational models\n* Machine teaching\n* Interpretable fine-grained models</p>\n\n<p>Multimodal learning\n* Using audio and video data\n* Using geographical priors\n* Using shape/3D information</p>\n\n<p>Fine-grained applications\n* Product recognition\n* Animal biometrics and camera traps\n* Museum collections e.g. biological, art, …</p>\n\n<p><strong>PAPER SUBMISSION DATES</strong></p>\n\n<p>Submission Deadline: <em>3rd April 2020</em>\nDecisions: <em>27th April 2020</em>\nCamera Ready Deadline: <em>7th May 2020</em>\nSubmission site: CMT URL will be available on our site soon <a href=\"https://sites.google.com/view/fgvc7/submission\">https://sites.google.com/view/fgvc7/submission</a></p>\n\n<p><strong>COVID-19</strong>\nThe current guidelines are that the CVPR 2020 organizers are still planning on a physical/hybrid meeting and that all workshops/tutorials are planned to take place as scheduled (see <a href=\"http://cvpr2020.thecvf.com/faq\">http://cvpr2020.thecvf.com/faq</a>). This is a changing situation, so please check the CVPR website for more up-to-date news. In the event of any disruptions, we will still be accepting papers which will be available on the FGVC website after our camera ready deadline and the FGVC competitions are still going ahead as planned. </p>\n\n<p><strong>COMPETITIONS</strong>\nWe will be holding six fine-grained computer vision challenges with tasks ranging from classification of attributes in art images through to classifying diseases in plants. The competitions are hosted on Kaggle. </p>\n\n<p>For more details please visit:\nFGVC <a href=\"https://sites.google.com/view/fgvc7\">https://sites.google.com/view/fgvc7</a></p>\n\n<p><strong>COMPETITION DATES</strong>\n* Competitions start: Mar 2020 <br>\n* Competitions end: May 2020 </p>",
  "messages": [
    {
      "id": 780934,
      "postDate": "2020-03-20T18:46:05.457Z",
      "content": "<p><strong>OVERVIEW</strong>\nFGVC7: The Seventh Workshop on Fine-Grained Visual Categorization\nJune 19th in conjunction with CVPR 2020, June, Seattle, USA.\nWebsite: <a href=\"https://sites.google.com/view/fgvc7\">https://sites.google.com/view/fgvc7</a>\nTwitter: @fgvcworkshop</p>\n\n<p>The purpose of this workshop is to bring together researchers to explore visual recognition across the continuum between basic level categorization (object recognition) and identification of individuals (face recognition, biometrics) within a category population. Participants are encouraged to submit short papers relevant to the workshop and to take part in a set of competitions organized in conjunction with the workshop - details below.</p>\n\n<p><strong>WORKSHOP DESCRIPTION</strong>\nFine-grained categorization (called `subordinate categorization’ in the psychology literature) lies in the continuum between basic-level categorization (object recognition) and the identification of individuals (e.g., face recognition, biometrics). The visual distinctions between similar categories are often quite subtle and therefore difficult to address with today’s general-purpose object recognition machinery. This is especially true for domains where data is not readily available on the web (e.g., medical images, or depth data), or domains for which training data is limited. It is likely that a radical re-thinking of the techniques used for representation learning, architecture design, human-in-the-loop learning, few-shot, and self-supervised learning that are currently used for visual recognition will be needed to improve fine-grained categorization.</p>\n\n<p>It is our hope that the invited talks, including researchers from scientific application domains, will shed light on human expertise and human performance in subordinate categorization and on motivating research applications. More information about previous FGVC workshops and competitions can be found at <a href=\"http://www.fgvc.org/\">http://www.fgvc.org/</a>.</p>\n\n<p><strong>PAPER SUBMISSION</strong>\nWe invite submission of 3 page (excluding references) extended abstracts (using the <a href=\"http://cvpr2020.thecvf.com/submission/main-conference/author-guidelines#submission-guidelines\">CVPR 2020</a> format) describing work in the domains suggested above or in closely-related areas. Accepted submissions will be presented as posters at the workshop. Reviewing of abstract submissions will be double-blind. The purpose of this workshop is not as a venue for publication, so much as a place to gather together those in the community working on or interested in FGVC. Submissions of work which has been previously published, including papers accepted to the main CVPR 2020 conference are allowed.</p>\n\n<p>For more details see - <a href=\"https://sites.google.com/view/fgvc7/submission\">https://sites.google.com/view/fgvc7/submission</a></p>\n\n<p>Topics of interest include the following:</p>\n\n<p>Fine-grained categorization\n* Novel datasets and data collection strategies for fine-grained categorization\n* Appropriate error metrics for fine-grained categorization\n* Low/few shot learning\n* Self-supervised learning\n* Transfer-learning from known to novel subcategories\n* Attribute and part based approaches\n* Taxonomic predictions</p>\n\n<p>Human-in-the-loop\n* Fine-grained categorization with humans in the loop\n* Embedding human experts’ knowledge into computational models\n* Machine teaching\n* Interpretable fine-grained models</p>\n\n<p>Multimodal learning\n* Using audio and video data\n* Using geographical priors\n* Using shape/3D information</p>\n\n<p>Fine-grained applications\n* Product recognition\n* Animal biometrics and camera traps\n* Museum collections e.g. biological, art, …</p>\n\n<p><strong>PAPER SUBMISSION DATES</strong></p>\n\n<p>Submission Deadline: <em>3rd April 2020</em>\nDecisions: <em>27th April 2020</em>\nCamera Ready Deadline: <em>7th May 2020</em>\nSubmission site: CMT URL will be available on our site soon <a href=\"https://sites.google.com/view/fgvc7/submission\">https://sites.google.com/view/fgvc7/submission</a></p>\n\n<p><strong>COVID-19</strong>\nThe current guidelines are that the CVPR 2020 organizers are still planning on a physical/hybrid meeting and that all workshops/tutorials are planned to take place as scheduled (see <a href=\"http://cvpr2020.thecvf.com/faq\">http://cvpr2020.thecvf.com/faq</a>). This is a changing situation, so please check the CVPR website for more up-to-date news. In the event of any disruptions, we will still be accepting papers which will be available on the FGVC website after our camera ready deadline and the FGVC competitions are still going ahead as planned. </p>\n\n<p><strong>COMPETITIONS</strong>\nWe will be holding six fine-grained computer vision challenges with tasks ranging from classification of attributes in art images through to classifying diseases in plants. The competitions are hosted on Kaggle. </p>\n\n<p>For more details please visit:\nFGVC <a href=\"https://sites.google.com/view/fgvc7\">https://sites.google.com/view/fgvc7</a></p>\n\n<p><strong>COMPETITION DATES</strong>\n* Competitions start: Mar 2020 <br>\n* Competitions end: May 2020 </p>",
      "rawMarkdown": "**OVERVIEW**\nFGVC7: The Seventh Workshop on Fine-Grained Visual Categorization\nJune 19th in conjunction with CVPR 2020, June, Seattle, USA.\nWebsite: https://sites.google.com/view/fgvc7\nTwitter: @fgvcworkshop\n\nThe purpose of this workshop is to bring together researchers to explore visual recognition across the continuum between basic level categorization (object recognition) and identification of individuals (face recognition, biometrics) within a category population. Participants are encouraged to submit short papers relevant to the workshop and to take part in a set of competitions organized in conjunction with the workshop - details below.\n\n**WORKSHOP DESCRIPTION**\nFine-grained categorization (called `subordinate categorization’ in the psychology literature) lies in the continuum between basic-level categorization (object recognition) and the identification of individuals (e.g., face recognition, biometrics). The visual distinctions between similar categories are often quite subtle and therefore difficult to address with today’s general-purpose object recognition machinery. This is especially true for domains where data is not readily available on the web (e.g., medical images, or depth data), or domains for which training data is limited. It is likely that a radical re-thinking of the techniques used for representation learning, architecture design, human-in-the-loop learning, few-shot, and self-supervised learning that are currently used for visual recognition will be needed to improve fine-grained categorization.\n\nIt is our hope that the invited talks, including researchers from scientific application domains, will shed light on human expertise and human performance in subordinate categorization and on motivating research applications. More information about previous FGVC workshops and competitions can be found at http://www.fgvc.org/.\n\n**PAPER SUBMISSION**\nWe invite submission of 3 page (excluding references) extended abstracts (using the [CVPR 2020](http://cvpr2020.thecvf.com/submission/main-conference/author-guidelines#submission-guidelines) format) describing work in the domains suggested above or in closely-related areas. Accepted submissions will be presented as posters at the workshop. Reviewing of abstract submissions will be double-blind. The purpose of this workshop is not as a venue for publication, so much as a place to gather together those in the community working on or interested in FGVC. Submissions of work which has been previously published, including papers accepted to the main CVPR 2020 conference are allowed.\n\nFor more details see - https://sites.google.com/view/fgvc7/submission\n\nTopics of interest include the following:\n\nFine-grained categorization\n* Novel datasets and data collection strategies for fine-grained categorization\n* Appropriate error metrics for fine-grained categorization\n* Low/few shot learning\n* Self-supervised learning\n* Transfer-learning from known to novel subcategories\n* Attribute and part based approaches\n* Taxonomic predictions\n\nHuman-in-the-loop\n* Fine-grained categorization with humans in the loop\n* Embedding human experts’ knowledge into computational models\n* Machine teaching\n* Interpretable fine-grained models\n\nMultimodal learning\n* Using audio and video data\n* Using geographical priors\n* Using shape/3D information\n\nFine-grained applications\n* Product recognition\n* Animal biometrics and camera traps\n* Museum collections e.g. biological, art, …\n\n**PAPER SUBMISSION DATES**\n\nSubmission Deadline: *3rd April 2020*\nDecisions: *27th April 2020*\nCamera Ready Deadline: *7th May 2020*\nSubmission site: CMT URL will be available on our site soon https://sites.google.com/view/fgvc7/submission\n\n**COVID-19**\nThe current guidelines are that the CVPR 2020 organizers are still planning on a physical/hybrid meeting and that all workshops/tutorials are planned to take place as scheduled (see http://cvpr2020.thecvf.com/faq). This is a changing situation, so please check the CVPR website for more up-to-date news. In the event of any disruptions, we will still be accepting papers which will be available on the FGVC website after our camera ready deadline and the FGVC competitions are still going ahead as planned. \n\n\n**COMPETITIONS**\nWe will be holding six fine-grained computer vision challenges with tasks ranging from classification of attributes in art images through to classifying diseases in plants. The competitions are hosted on Kaggle. \n\nFor more details please visit:\nFGVC https://sites.google.com/view/fgvc7\n\n**COMPETITION DATES**\n* Competitions start: Mar 2020  \n* Competitions end: May 2020 ",
      "votes": 1
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    "780934": "**OVERVIEW**\nFGVC7: The Seventh Workshop on Fine-Grained Visual Categorization\nJune 19th in conjunction with CVPR 2020, June, Seattle, USA.\nWebsite: https://sites.google.com/view/fgvc7\nTwitter: @fgvcworkshop\n\nThe purpose of this workshop is to bring together researchers to explore visual recognition across the continuum between basic level categorization (object recognition) and identification of individuals (face recognition, biometrics) within a category population. Participants are encouraged to submit short papers relevant to the workshop and to take part in a set of competitions organized in conjunction with the workshop - details below.\n\n**WORKSHOP DESCRIPTION**\nFine-grained categorization (called `subordinate categorization’ in the psychology literature) lies in the continuum between basic-level categorization (object recognition) and the identification of individuals (e.g., face recognition, biometrics). The visual distinctions between similar categories are often quite subtle and therefore difficult to address with today’s general-purpose object recognition machinery. This is especially true for domains where data is not readily available on the web (e.g., medical images, or depth data), or domains for which training data is limited. It is likely that a radical re-thinking of the techniques used for representation learning, architecture design, human-in-the-loop learning, few-shot, and self-supervised learning that are currently used for visual recognition will be needed to improve fine-grained categorization.\n\nIt is our hope that the invited talks, including researchers from scientific application domains, will shed light on human expertise and human performance in subordinate categorization and on motivating research applications. More information about previous FGVC workshops and competitions can be found at http://www.fgvc.org/.\n\n**PAPER SUBMISSION**\nWe invite submission of 3 page (excluding references) extended abstracts (using the [CVPR 2020](http://cvpr2020.thecvf.com/submission/main-conference/author-guidelines#submission-guidelines) format) describing work in the domains suggested above or in closely-related areas. Accepted submissions will be presented as posters at the workshop. Reviewing of abstract submissions will be double-blind. The purpose of this workshop is not as a venue for publication, so much as a place to gather together those in the community working on or interested in FGVC. Submissions of work which has been previously published, including papers accepted to the main CVPR 2020 conference are allowed.\n\nFor more details see - https://sites.google.com/view/fgvc7/submission\n\nTopics of interest include the following:\n\nFine-grained categorization\n* Novel datasets and data collection strategies for fine-grained categorization\n* Appropriate error metrics for fine-grained categorization\n* Low/few shot learning\n* Self-supervised learning\n* Transfer-learning from known to novel subcategories\n* Attribute and part based approaches\n* Taxonomic predictions\n\nHuman-in-the-loop\n* Fine-grained categorization with humans in the loop\n* Embedding human experts’ knowledge into computational models\n* Machine teaching\n* Interpretable fine-grained models\n\nMultimodal learning\n* Using audio and video data\n* Using geographical priors\n* Using shape/3D information\n\nFine-grained applications\n* Product recognition\n* Animal biometrics and camera traps\n* Museum collections e.g. biological, art, …\n\n**PAPER SUBMISSION DATES**\n\nSubmission Deadline: *3rd April 2020*\nDecisions: *27th April 2020*\nCamera Ready Deadline: *7th May 2020*\nSubmission site: CMT URL will be available on our site soon https://sites.google.com/view/fgvc7/submission\n\n**COVID-19**\nThe current guidelines are that the CVPR 2020 organizers are still planning on a physical/hybrid meeting and that all workshops/tutorials are planned to take place as scheduled (see http://cvpr2020.thecvf.com/faq). This is a changing situation, so please check the CVPR website for more up-to-date news. In the event of any disruptions, we will still be accepting papers which will be available on the FGVC website after our camera ready deadline and the FGVC competitions are still going ahead as planned. \n\n\n**COMPETITIONS**\nWe will be holding six fine-grained computer vision challenges with tasks ranging from classification of attributes in art images through to classifying diseases in plants. The competitions are hosted on Kaggle. \n\nFor more details please visit:\nFGVC https://sites.google.com/view/fgvc7\n\n**COMPETITION DATES**\n* Competitions start: Mar 2020  \n* Competitions end: May 2020 "
  }
}