• Publications
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Improving Object Localization with Fitness NMS and Bounded IoU Loss
We demonstrate that many detection methods are designed to identify only a sufficently accurate bounding box, rather than the best available one. To address this issue we propose a simple and fastExpand
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Statistical Threat Assessment for General Road Scenes Using Monte Carlo Sampling
  • A. Eidehall, L. Petersson
  • Computer Science, Engineering
  • IEEE Transactions on Intelligent Transportation…
  • 1 March 2008
This paper presents a threat-assessment algorithm for general road scenes. A road scene consists of a number of objects that are known, and the threat level of the scene is based on their currentExpand
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Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation
Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently, CNN-based methodsExpand
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Encouraging LSTMs to Anticipate Actions Very Early
In contrast to the widely studied problem of recognizing an action given a complete sequence, action anticipation aims to identify the action from only partially available videos. As such, it isExpand
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GOGMA: Globally-Optimal Gaussian Mixture Alignment
Gaussian mixture alignment is a family of approaches that are frequently used for robustly solving the point-set registration problem. However, since they use local optimisation, they are susceptibleExpand
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A new pedestrian dataset for supervised learning
This paper presents a comparative analysis of different pedestrian dataset characteristics. The main goal of the research is to determine what characteristics are desirable for improved training andExpand
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DeNet: Scalable Real-Time Object Detection with Directed Sparse Sampling
We define the object detection from imagery problem as estimating a very large but extremely sparse bounding box dependent probability distribution. Subsequently we identify a sparse distributionExpand
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Large scale sign detection using HOG feature variants
In this paper we present two variant formulations of the well-known Histogram of Oriented Gradients (HOG) features and provide a comparison of these features on a large scale sign detection problem.Expand
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An Adaptive Data Representation for Robust Point-Set Registration and Merging
This paper presents a framework for rigid point-set registration and merging using a robust continuous data representation. Our point-set representation is constructed by training a one-class supportExpand
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High-level control of a mobile manipulator for door opening
In this paper, off-the-shelf algorithms for force/torque control are used in the context of mobile manipulation, in particular, the task of opening a door is studied. To make the solution robust, asExpand
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