3 accepted papers
In order to balance the detection time and accuracy, the state-of-the-art region-based detectors use a fixed number of proposals to obtain detection results in the inference phase. However, in surveillance scenes, object population varies in different images, causing the fixed proposal number become…
Vehicle license plate (VLP) super-resolution (SR) is of great demand in intelligent traffic systems. Super-Resolution for extremely low-resolution VLP remains challenging and the state-of-the-art SR methods hardly provide satisfying results for low-resolution (LR) VLPs. In this study, from a new per…
Though tremendous progresses have been made in object detection due to the deep convolutional networks, one of the remaining challenges is the multi-scale object detection(MOD). To improve the performance of MOD task, we take Faster region-based CNN (Faster R-CNN) framework and work on two specific…