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Houqiang Li

Researcher at University of Science and Technology of China

Publications -  612
Citations -  17591

Houqiang Li is an academic researcher from University of Science and Technology of China. The author has contributed to research in topics: Computer science & Motion compensation. The author has an hindex of 57, co-authored 520 publications receiving 12325 citations. Previous affiliations of Houqiang Li include China University of Science and Technology & Nanjing Medical University.

Papers
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Proceedings ArticleDOI

Convolutional Neural Network-Based Motion Compensation Refinement for Video Coding

TL;DR: This work studies a simple CNN-based motion compensation refinement (CNNMCR) scheme, and proposes a more powerful CNNMCR scheme, where the CNN utilizes not only the motion compensated prediction, but also the neighboring reconstructed region to refine the prediction.
Proceedings ArticleDOI

Video Coding with Spatio-Temporal Texture Synthesis

TL;DR: A video coding scheme in which some texture regions are selectively removed at the encoder and recovered by synthesis at the decoder, integrated into H.264/AVC and achieves up to 38.8% bitrate saving at similar visual quality levels compared with H.265.
Journal ArticleDOI

Foxp3+ T regulatory cells (Tregs) are increased in nasal polyps (NP) after treatment with intranasal steroid.

TL;DR: Foxp3 is downregulated in NP and intranasal steroid attenuates the chronic inflammatory response by enhancing the expression and function of Foxp3 in NP.
Proceedings ArticleDOI

Video coding with spatio-temporal texture synthesis and edge-based inpainting

TL;DR: A video coding scheme, in which textural and structural regions are selectively removed in the encoder, and restored in the decoder by spatio-temporal texture synthesis and edge-based inpainting, which achieves up to 35% bitrate saving at similar visual quality levels compared with H.264/AVC without this approach.
Journal ArticleDOI

Rate-Distortion Optimized Reference Picture Management for High Efficiency Video Coding

TL;DR: This paper investigates how to manage reference pictures so as to achieve better rate-distortion performance under the memory constraint of the decoded picture buffer at the decoder, and forms the reference picture management as an optimization problem and approximate its optimal solution.