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             <h2 class="col-md-12 text-center">
 			Neural Implicit Representation for Building Digital Twins of <br>
 			Unknown Articulated Objects
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                 <small>
-                    Anonymous Submission
+                  Yijia Weng, Bowen Wen, Jonathan Tremblay, Valts Blukis
+                  </br>
+                  Dieter Fox, Leonidas Guibas, Stan Birchfield
                 </small>
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 				<br><br>
                 <p class="text-justify">
 				Our reconstructed digital twin can be readily imported into simulation environments and interacted with. The above video shows an example interaction sequence in Issac Gym, played at 4x speed.
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 				<br><br>
                 <p class="text-justify">
 				Visualization of reconstruction results on PARIS Two-Part Object Dataset from PARIS, PARIS* (PARIS augmented with depth supervision), and our method. We run each method 10 times with different random initializations and show typical trials with performance closest to the average.
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 				<br><br>
                 <p class="text-justify">
 				Visualization of reconstruction results on SAPIEN Multi-Part Objects from PARIS*-m (PARIS augmented with depth supervision and extended to handle multiple movable parts) and our method. We run each method 10 times with different random initializations and show typical trials with performance closest to the average.
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