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@@ -350,30 +350,6 @@ <h2 class="title is-3">Abstract</h2>
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-<section class="section">
-    <div class="container is-max-desktop">
-          <center><h2 class="title is-3">Experiment Results</h2></center>
-    <center><img src="./static/images/reconstr_vis.png"></center>
-    Quantitative comparison with existing methods on HQSeg-44K and DAVIS. We compare two types of baselines: specialist and
-    generalist models. Our model achieves comparable performance to the specialist baselines but with significantly lower latency; our model
-    achieves comparable performance to the generalist models in terms of latency and segmentation quality despite being trained with much
-    fewer segmentation data. “HQ” denotes the HQSeg-44K dataset; “SA×2” denotes the model has two self-attention blocks for dense fusion. 
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-    <br><br><br>
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-    <center><img src="./static/images/transfer_quant.png"></center>
-    Qualitative results with diverse prompts. Left: an example from DAVIS. Right: three examples from HQSeg-44K. The results 
-    are achieved by a user providing all the prompts using our best-performing model.
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-    <br><br><br>
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-    <center><img src="./static/images/transfer_vis.png"></center>
-    Qualitative results with diverse prompts. Left: an example from DAVIS. Right: three examples from HQSeg-44K. The results
-    are achieved by a user providing all the prompts using our best-performing model.
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-  </div>
-</section>
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 <section class="section" id="BibTeX">
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