Try this demo for MSL, introduced in our WACV 2024 paper Learning to Recognize Occluded and Small Objects with Partial Inputs.
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.
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")
Project Page