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    Dear all,<br>
    <br>
    We are happy to announce that the CORe50 dataset from the paper “<i>CORe50:
      a new Dataset and Benchmark for Continuous Object Recognition</i>”
    (CoRL, 2017) is now publicly available at the link: <a
      href="https://vlomonaco.github.io/core50/">https://vlomonaco.github.io/core50/</a><br>
    <br>
    <b>CORe50</b>, specifically designed for <i>Continuous/Lifelong
      Learning</i> and <i>Object Recognition</i>, is a collection of
    more than 500 videos (30fps) of 50 domestic objects belonging to 10
    different categories. Instance level granularity, temporal
    coherence, first-person point-of-view and very different
    environmental conditions and backgrounds (outdoor sessions included)
    is what makes CORe50 particularly useful for assessing <i>Continuous
      Learning</i> techniques.<br>
    <br>
    On top of the CORe50 dataset we are also happy to release a 3-way
    benchmark with multiple baselines and a living leaderboard to keep
    track of the progresses made in this new exciting area! For
    downloading the code, the dataset, the benchmark and more, check out
    the official website <a href="https://vlomonaco.github.io/core50/">https://vlomonaco.github.io/core50/</a><br>
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              Best regards,<br>
              Vincenzo<br>
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            <span><span style="color:rgb(68,68,68)">Vincenzo Lomonaco,
                M.Sc.</span></span></div>
          <div style="text-align:center"><span><span
                style="color:rgb(68,68,68)">PhD Students' Representative
                @ DISI, University of Bologna</span><br>
              <span><span style="color:rgb(68,68,68)"><a
                    href="http://www.vincenzolomonaco.com/"
                    target="_blank">http://www.vincenzolomonaco.com/</a></span></span></span></div>
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