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msl-recognition-demo

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hasibzunair commited on Nov 2, 2023

Commit

e441600

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1 Parent(s): 39529e8

add paper link

Files changed (2) hide show

app.py CHANGED Viewed

@@ -83,7 +83,7 @@ inputs = gr.inputs.Image(type="filepath", label="Input Image")
 # Define style
 title = "Learning to Recognize Occluded and Small Objects with Partial Inputs"
 description = codecs.open("description.html", "r", "utf-8").read()
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1512.03385' target='_blank'>Learning to Recognize Occluded and Small Objects with Partial Inputs</a> | <a href='https://github.com/hasibzunair/msl-recognition' target='_blank'>Github Repo</a></p>"
 voc_classes = ("aeroplane", "bicycle", "bird", "boat", "bottle",
            "bus", "car", "cat", "chair", "cow", "diningtable",

 # Define style
 title = "Learning to Recognize Occluded and Small Objects with Partial Inputs"
 description = codecs.open("description.html", "r", "utf-8").read()
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2310.18517' target='_blank'>Learning to Recognize Occluded and Small Objects with Partial Inputs</a> | <a href='https://github.com/hasibzunair/msl-recognition' target='_blank'>Github Repo</a></p>"
 voc_classes = ("aeroplane", "bicycle", "bird", "boat", "bottle",
            "bus", "car", "cat", "chair", "cow", "diningtable",

description.html CHANGED Viewed

@@ -6,7 +6,7 @@
 </head>
 <body>
     Try this demo for <a href="https://github.com/hasibzunair/msl-recognition">MSL</a>,
-    introduced in our <strong>WACV 2024</strong> paper <a href="ADD_PAPER_LINK">Learning to Recognize Occluded and Small Objects with Partial Inputs</a>.
     </br>
     MSL aims to explicitly focus on context from neighbouring regions around objects. Further,
     this also enables to learn a distribution of association across classes. Ideally to handle

 </head>
 <body>
     Try this demo for <a href="https://github.com/hasibzunair/msl-recognition">MSL</a>,
+    introduced in our <strong>WACV 2024</strong> paper <a href="https://arxiv.org/abs/2310.18517">Learning to Recognize Occluded and Small Objects with Partial Inputs</a>.
     </br>
     MSL aims to explicitly focus on context from neighbouring regions around objects. Further,
     this also enables to learn a distribution of association across classes. Ideally to handle