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README.md
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@@ -70,54 +70,17 @@ io = gr.Interface(fn=predict, inputs=inputs, outputs=outputs)
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If you need help creating a Gradio Interface for your model, check out the Gradio Getting Started guide.
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</p>
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<p class="lg:col-span-2">
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Note: Commercial sales and marketing activities are not appropriate for submissions in the CVPR Demo Track and should be arranged as part of the CVPR Exhibit Program.
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</p>
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<h4 class="my-8 lg:col-span-2" style="font-size:20px; font-weight:bold">Best Demo Awards
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</h4>
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<p class="lg:col-span-2">
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CVPR 2022’s demo track will feature Best Demo Awards. We hope to encourage researchers to create interactive systems based on cutting-edge research that is publicly available, fun, useful, and easy-to-use.
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</p>
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<h4 class="my-8 lg:col-span-2" style="font-size:20px; font-weight:bold">Important Dates
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<ul class="lg:col-span-2" style="list-style: circle inside">
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<li class="my-4">Paper registration deadline Round 1: (Late registrations will require organizer permission): Jan 31, 2022
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</li>
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<li class="my-4">Paper submission deadline Round 1: Feb 7, 2022
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</li>
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<li class="my-4">Notification of acceptance Round 1: March 8, 2022
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</li>
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<li class="my-4">Paper registration deadline Round 2 (fast track for CVPR): March 18, 2022
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</li>
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<li class="my-4">Paper submission deadline Round 2 : March 20, 2022
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</li>
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<li class="my-4">Camera-ready submission: April 18, 2022
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</li>
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</ul>
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<h4 class="my-8 lg:col-span-2" style="font-size:20px; font-weight:bold">All deadlines are 11.59 pm Pacific Time
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</h4>
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<p class="lg:col-span-2">
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The proposed system needs to be ready at Camera-Ready time. Additional improvements are allowed, but should not diverge significantly from the published description in the paper.
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</p>
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<p class="lg:col-span-2">
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Note: we encourage authors to submit to Round 1 if possible. For Round 2, we focus on fast track for accepted/rejected CVPR main conference papers. Each demo paper based on a previous CVPR submission should be submitted along with the CVPR paper submission, reviews and decisions.
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</p>
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</div>
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If you need help creating a Gradio Interface for your model, check out the Gradio Getting Started guide.
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</p>
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<h3 class="my-8 lg:col-span-2" style="font-size:20px; font-weight:bold">4. Then launch() you Interface to confirm that it runs correctly locally (or wherever you are running Python)
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</h3>
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<pre>
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<code>
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io.launch()
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</code>
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</pre>
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<p class="lg:col-span-2">
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You should see a web interface like the following where you can drag and drop your data points and see the predictions:
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</p>
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<img class="lg:col-span-2" src="https://lh6.googleusercontent.com/xABSrPaS-fgtPNy-TDueab_0mgIui02NYqHyxgGG84zf22FnxUcj5Cgxv4Wayk0bfDqkZ4965uRdg9LLB-ur-MAhnb9K5PJbCAzx_6QuSPKZFsMlqqaogCB1n55j6PnKL9HJ6NZf" alt="Gradio Interface" style="margin:10px">
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</div>
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