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| 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>. | |
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| 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 | |
| situations in-the-wild where only part of some object class is visible, but where us humans might | |
| readily use context to infer the classes presence. | |
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| You can use this demo to get the a list of objects present in your images. To use it, simply | |
| upload an image of your choice and hit submit. You will get one or more names of objects present | |
| in your images from this list: | |
| ("aeroplane", "bicycle", "bird", "boat", "bottle", | |
| "bus", "car", "cat", "chair", "cow", "diningtable", | |
| "dog", "horse", "motorbike", "person", "pottedplant", | |
| "sheep", "sofa", "train", "tvmonitor") | |
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| <a href="https://hasibzunair.github.io/msl-recognition/">Project Page</a> | |
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