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Improving Object Localization with Fitness NMS and Bounded IoU Loss
TLDR
We demonstrate that many detection methods are designed to identify only a sufficently accurate bounding box, rather than the best available one. Expand
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DeNet: Scalable Real-Time Object Detection with Directed Sparse Sampling
TLDR
We define the object detection from imagery problem as estimating a very large but extremely sparse bounding box dependent probability distribution. Expand
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Creating robust high-throughput traffic sign detectors using centre-surround HOG statistics
TLDR
In this paper, we detail a system for creating object detectors which meet the extreme demands of real-world traffic sign detection applications such as GPS map making and real-time in-car Traffic sign detection. Expand
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Heterogeneous Ground and Air Platforms, Homogeneous Sensing: Team CSIRO Data61's Approach to the DARPA Subterranean Challenge
TLDR
Heterogeneous teams of robots, leveraging a balance between autonomy and human interaction, bring powerful capabilities to the problem of exploring dangerous, unstructured subterranean environments. Expand
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