{"id":3174,"date":"2023-06-29T08:21:52","date_gmt":"2023-06-29T08:21:52","guid":{"rendered":"https:\/\/metricsproject.eu\/?page_id=3174"},"modified":"2024-10-28T12:36:38","modified_gmt":"2024-10-28T12:36:38","slug":"2nd-cascade-campaign-2023","status":"publish","type":"page","link":"https:\/\/metricsproject.eu\/agile-production\/2nd-cascade-campaign-2023\/","title":{"rendered":"2nd Cascade Campaign 2023"},"content":{"rendered":"
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ADAPT Cascade Competition<\/strong><\/h3>\n

Sim2Real object Detection and Pose-Estimation Challenge<\/em><\/strong><\/p>\n

We were pleased to invite you to join the ADAPT Cascade Competition dedicated to the benchmarking and testing Machine Learning algorithms and solutions for typical industrial challenges.<\/p>\n

In this Cascade competition, using simulation data,<\/em> two main benchmarks will be used to test and evaluate the competitor\u2019s solutions for Object Detection and Classification and Pose-Estimation of typical industrial parts.<\/p>\n

How to participate<\/strong><\/h3>\n
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  1. Create an account on Codalab<\/li>\n
  2. Join the challenge\n
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    1. Object Detection and Classification: https:\/\/codalab.lisn.upsaclay.fr\/competitions\/15873<\/a><\/li>\n
    2. Pose-Estimation of typical industrial parts: https:\/\/codalab.lisn.upsaclay.fr\/competitions\/15874<\/a><\/li>\n<\/ol>\n<\/li>\n
    3. Download the datasets provided in the link on Codalab<\/li>\n
    4. Submit results for the validation<\/li>\n<\/ol>\n

      Representative images<\/strong><\/p>\n

      \"\"<\/h3>\n

      Results<\/strong><\/h3>\n\n\n\n\n\n\n
      User<\/strong><\/td>\nTotal Submissions<\/strong><\/td>\nSuccessful<\/strong><\/td>\nFailed<\/strong><\/td>\n<\/tr>\n
      Giwan<\/td>\n11<\/td>\n11<\/td>\n0<\/td>\n<\/tr>\n
      stefiOns<\/td>\n18<\/td>\n13<\/td>\n5<\/td>\n<\/tr>\n
      Total<\/strong><\/td>\n29<\/strong><\/td>\n24<\/strong><\/td>\n5<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      Awards<\/h3>\n

      Please be informed that the winner of each of the two ongoing ADAPT Sim2Real competitions for Object Detection and Pose Estimation will be awarded with a \u201cCEA-Moonshot Prize\u201d to attend a Major International Conference to be announced<\/b>.<\/strong><\/p>\n

      The Prizes, limited to 2000\u20ac per winning team (or individual) will be paid in the form of reimbursement of the costs of travel, subsistence and conference registration fees upon submission of receipts along with a travel expense claim form. A certificate will also be provided to the awardees during the conference.<\/p>\n<\/div>\n<\/div><\/div><\/div>

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      Important dates:<\/h3>\n\n\n\n\n\n
      Validation phase<\/td>\n27.09.2023 - 05.11.2023<\/td>\n<\/tr>\n
      Test phase<\/td>\n06.11.2023 - 17.11.2023<\/td>\n<\/tr>\n
      Results announcement<\/td>\nby 30.11.2023<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div><\/div><\/div>
      \n
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      More information:<\/h3>\n

      For more information, please contact agile.production(a)metricsproject.eu<\/a><\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"

      ADAPT Cascade Competition Sim2Real object Detection and Pose-Estimation Challenge We were pleased to invite you to join the ADAPT Cascade Competition dedicated to the benchmarking and testing Machine Learning algorithms and solutions for typical industrial challenges. In this Cascade competition, using simulation data, two main benchmarks will be used to test and evaluate the competitor\u2019s […]<\/p>\n","protected":false},"author":4,"featured_media":647,"parent":100,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"templates\/agile-page.php","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/pages\/3174"}],"collection":[{"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/comments?post=3174"}],"version-history":[{"count":6,"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/pages\/3174\/revisions"}],"predecessor-version":[{"id":3436,"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/pages\/3174\/revisions\/3436"}],"up":[{"embeddable":true,"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/pages\/100"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/media\/647"}],"wp:attachment":[{"href":"https:\/\/metricsproject.eu\/wp-json\/wp\/v2\/media?parent=3174"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}