Object detection-the computer vision task dealing with detecting instances of objects of a
certain class (eg,'car','plane', etc.) in images-attracted a lot of attention from the community …

Learning to solve complex sequences of tasks--while both leveraging transfer and avoiding
catastrophic forgetting--remains a key obstacle to achieving human-level intelligence. The …

The goal of this paper is to perform 3D object detection in the context of autonomous driving.
Our method aims at generating a set of high-quality 3D object proposals by exploiting stereo …

Training a generic objectness measure to produce a small set of candidate object windows,
has been shown to speed up the classical sliding window object detection paradigm. We …

Abstract Development of region proposal algorithms has rapidly become one of the most
critical research areas over recent years. The perfect accuracy of region-based recognition …

Object proposals have recently emerged as an essential cornerstone for object detection.
The current state-of-the-art object detectors employ object proposals to detect objects within …

The problem of computing category agnostic bounding box proposals is utilized as a core
component in many computer vision tasks and thus has lately attracted a lot of attention. In …

Traffic light recognition is one of the important tasks in the studies of intelligent transport
system. In this paper, a robust traffic light recognition model based on vision information is …

Object proposals have quickly become the de-facto pre-processing step in a number of
vision pipelines (for object detection, object discovery, and other tasks). Their performance is …

Use of the object proposal method as a preprocessing step for object detection of vision
sensors has improved computational efficiency in recent years. Good object proposal …