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Chong Luo

Researcher at Microsoft

Publications -  108
Citations -  5190

Chong Luo is an academic researcher from Microsoft. The author has contributed to research in topics: Decoding methods & Communication channel. The author has an hindex of 29, co-authored 106 publications receiving 3990 citations. Previous affiliations of Chong Luo include Shanghai Jiao Tong University & University of Science and Technology of China.

Papers
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Book ChapterDOI

The sixth visual object tracking VOT2018 challenge results

Matej Kristan, +158 more
TL;DR: The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative; results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years.
Proceedings ArticleDOI

Compressive data gathering for large-scale wireless sensor networks

TL;DR: This paper presents the first complete design to apply compressive sampling theory to sensor data gathering for large-scale wireless sensor networks and shows the efficiency and robustness of the proposed scheme.
Proceedings ArticleDOI

A Twofold Siamese Network for Real-Time Object Tracking

TL;DR: The proposed SA-Siam outperforms all other real-time trackers by a large margin on OTB-2013/50/100 benchmarks and proposes a channel attention mechanism for the semantic branch.
Journal ArticleDOI

Multimedia Cloud Computing

TL;DR: A multimedia-aware cloud is presented, which addresses how a cloud can perform distributed multimedia processing and storage and provide quality of service (QoS) provisioning for multimedia services, and a media-edge cloud (MEC) architecture is proposed, in which storage, central processing unit (CPU), and graphics processing units (GPU) clusters are presented at the edge.
Proceedings ArticleDOI

The Seventh Visual Object Tracking VOT2019 Challenge Results

Matej Kristan, +179 more
TL;DR: The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative; results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years.