Titlebook: Computer Vision – ACCV 2018; 14th Asian Conferenc C.V. Jawahar,Hongdong Li,Konrad Schindler Conference proceedings 2019 Springer Nature Swi

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Peter Bogach Greenspan DO, FACOG, FACSLarge FoV cameras are beneficial for large-scale outdoor SLAM applications, because they increase visual overlap between consecutive frames and capture more pixels belonging to the static parts of the environment. However, current feature-based SLAM systems such as PTAM and ORB-SLAM limit their came

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CT Study of Lesions Near the Skull Basetical CCTV surveillance scenario, where full person views are often unavailable. Missing body parts make the comparison very challenging due to significant misalignment and varying scale of the views. We propose Partial Matching Net (PMN) that detects body joints, aligns partial views and hallucinat

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S. Wende,A. Aulich,E. Schindlerghly desired, existing methods require strict capture restriction such as modulated active light. Here, we propose the first method to infer both components from a single image without any hardware restriction. Our method is a novel generative adversarial network (GAN) based networks which imposes p

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https://doi.org/10.1007/978-94-007-5380-8ingle dataset but fail to generalize well on another datasets. The emerging problem mainly comes from style difference between two datasets. To address this problem, we propose a novel style transfer framework based on Generative Adversarial Networks (GAN) to generate target-style images. Specifical

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On Boundaries of the Language of Physics, encoder-decoder framework. While the commonly adopted image encoder (e.g., CNN network), might be capable of extracting image features to the desired level, interpreting these abstract image features into hundreds of tokens of code puts a particular challenge on the decoding power of the RNN-based