H
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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Journal ArticleDOI
Progressive Unsupervised Person Re-Identification by Tracklet Association With Spatio-Temporal Regularization
TL;DR: Wang et al. as discussed by the authors proposed a progressive deep learning method for unsupervised person ReID in the wild by Tracklet Association with Spatio-Temporal Regularization (TASTR).
Proceedings ArticleDOI
Boosting Continuous Sign Language Recognition via Cross Modality Augmentation
TL;DR: This work proposes a novel architecture with cross modality augmentation for continuous sign language recognition that can be easily extended to other existing CTC based continuous SLR architectures and validates the effectiveness of the proposed method on two continuousSLR benchmarks.
Proceedings ArticleDOI
A Hybrid Neural Network for Chroma Intra Prediction
TL;DR: This paper proposes a chroma intra prediction method by exploiting both spatial and cross-channel correlations using a hybrid neural network, utilizing a convolutional neural network to extract features from the reconstructed luma samples of the current block, as well as utilize a fully connected network.
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Block-Composed Background Reference for High Efficiency Video Coding
TL;DR: A block-composed background reference method is proposed in this paper for High Efficiency Video Coding (HEVC), which makes the scheme free of bit-rate burst and more suitable for real-time applications and can generate high-quality background reference even with complicated foreground.
Journal ArticleDOI
Efficient Projected Frame Padding for Video-Based Point Cloud Compression
TL;DR: This paper designs padding algorithms tailored to each group of unoccupied pixels and proposes padding the residue of these pixels using the average residue of the occupied pixels in order to reduce the residue bitrate as much as possible.