Object detection in crowded scenes is challenging. When objects gather, they tend to overlap largely with each other, leading to occlusions. Occlusion caused by objects of the same class is called intra-class occlusion, also referred to as crowd occlusion. Object detectors need to determine the locations of different objects in the crowd and accurately delineate their … [Read more...] about Deep-Learning Based Object Detection in Crowded Scenes
Single Stage Instance Segmentation – A Review
Instance segmentation is a challenging computer vision task that requires the prediction of object instances and their per-pixel segmentation mask. This makes it a hybrid of semantic segmentation and object detection. Ever since Mask R-CNN was invented, the state-of-the-art method for instance segmentation has largely been Mask RCNN and its variants … [Read more...] about Single Stage Instance Segmentation – A Review
Convolutional Neural Networks With Heterogeneous Metadata
In autonomous driving, convolutional neural networks are the go-to tool for various perception tasks. Although CNNs are great at distilling information from camera images (or a sequence of them in form of a video clip), I constantly bump into all kinds of metadata that do not lend themselves to convolutional neural networks. Metadata, by traditional definition, means a set … [Read more...] about Convolutional Neural Networks With Heterogeneous Metadata