Drones equipped with cameras can significantly enhance human's ability to perceive the world because of their remarkable maneuverability in 3D space. Ironically, object detection for drones has always been conducted 2D image space, which fundamentally limits understand scenes. Furthermore, existing methods developed autonomous driving cannot be directly applied due lack deformation modeling, is...

We present an object detection based approach to localize handwritten regions from documents, which initially aims enhance the anonymization during data transmission. The concatenated fusion of original and preprocessed images containing both printed texts notes or signatures are fed into convolutional neural network, where bounding boxes learned detect handwriting. Afterwards, can be processed...

This paper proposes anchor pruning for object detection in one-stage anchor-based detectors. While techniques are widely used to reduce the computational cost of convolutional neural networks, they tend focus on optimizing backbone networks where often most computations are. In this work we demonstrate an additional technique, specifically detection: pruning. With more efficient and a growing t...