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Deep Convolutional Neural Networks (CNN) are the state-of-the-art performers for the object detection task. It is well known that object detection requires more com- putation and memory than image classification. In this work, we propose LCDet, a fully-convolutional neural net- work for generic object detection that aims to work in em- bedded systems. We design and develop an end-to-end TensorFlow(TF)-based...
Object proposals for detecting moving or static video objects need to address issues such as speed, memory complexity and temporal consistency. We propose an efficient Video Object Proposal (VOP) generation method and show its efficacy in learning a better video object detector A deep-learning based video object detector learned using the proposed VOP achieves state-of-the-art detection performance...
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