G
Guo-Jun Qi
Researcher at Huawei
Publications - 263
Citations - 12701
Guo-Jun Qi is an academic researcher from Huawei. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 53, co-authored 248 publications receiving 9928 citations. Previous affiliations of Guo-Jun Qi include China University of Science and Technology & University of Science and Technology of China.
Papers
More filters
Journal ArticleDOI
Self-similarity Driven Scale-invariant Learning for Weakly Supervised Person Search
TL;DR: Wang et al. as discussed by the authors proposed a self-similarity driven scale-invariant learning (SSL) framework, which explores scale invariance based on the selfsimilarity prior that it shows the same statistical properties of an image at different scales.
Proceedings ArticleDOI
A 3-D wafer level hermetical packaging for MEMS
TL;DR: In this article, a 3D wafer-level hermetical packaging solution for microelectromechanical-system (MEMS) is presented, where the MEMS wafer is sandwiched between a top glass wafer and a bottom Si substrate wafer with the assistance of a gold intermediate layer.
Patent
An integrated shadow mask and method of fabrication thereof
TL;DR: An integrated shadow mask (100) comprises a substrate (112), at least one pillar structure (106) having a b portion (114) and an overhang portion (104) supported by the base portion.
Posted Content
Self-Supervised Graph Representation Learning via Topology Transformations.
Xiang Gao,Wei Hu,Guo-Jun Qi +2 more
TL;DR: In this paper, the authors proposed the Topology Transformation Equivariant Representation Learning (TESL) method, which maximizes the mutual information between topology transformations and node representations before and after the transformations.
Book ChapterDOI
Clustering Multimedia Data
TL;DR: In this paper, the authors discuss the clustering techniques that have been applied to wide variety of image data, including the application to visual words learning, and explain different clustering algorithms used in the context of video and audio data, such as video summarization, video event detection, video story clustering and music summarization.