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MUlti-Store Tracker (MUSTer): A cognitive psychology inspired approach to object tracking
Variations in the appearance of a tracked object, such as changes in geometry/photometry, camera viewpoint, illumination, or partial occlusion, pose a major challenge to object tracking. Here, weExpand
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An Experimental Survey on Correlation Filter-based Tracking
Over these years, Correlation Filter-based Trackers (CFTs) have aroused increasing interests in the field of visual object tracking, and have achieved extremely compelling results in differentExpand
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RBNet: A Deep Neural Network for Unified Road and Road Boundary Detection
Accurately detecting road and its boundary on the images is an essential task for vision-based autonomous driving systems. However, prevailing methods either only detect road or add an extraExpand
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Context Refinement for Object Detection
Current two-stage object detectors, which consists of a region proposal stage and a refinement stage, may produce unreliable results due to ill-localized proposed regions. To address this problem, weExpand
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Progressive LiDAR adaptation for road detection
Despite rapid developments in visual image-based road detection, robustly identifying road areas in visual images remains challenging due to issues like illumination changes and blurry images. ToExpand
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The Visual Object Tracking VOT 2015 Challenge Results
The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers areExpand
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Generic Pixel Level Object Tracker Using Bi-Channel Fully Convolutional Network
As most of the object tracking algorithms predict bounding boxes to cover the target, pixel-level tracking methods provide a better description of the target. However, it remains challenging for aExpand
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ASTS: A Unified Framework for Arbitrary Shape Text Spotting
Arbitrary shape text spotting remains a challenging computer vision task. In this paper, we propose an end-to-end trainable unified framework for arbitrary shape text spotting to overcome theExpand
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Analysis and Optimization of the Implicit Broadcasts in FPGA HLS to Improve Maximum Frequency
Designs generated by high-level synthesis (HLS) tools typically achieve a lower frequency compared to manual RTL designs. In this work, we study the timing issues in a diverse set of realistic andExpand
A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection
Deep learning-based computer vision is usually data-hungry. Many researchers attempt to augment datasets with synthesized data to improve model robustness. However, the augmentation of popularExpand
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