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Fumin Shen
Researcher at University of Electronic Science and Technology of China
Publications - 244
Citations - 11134
Fumin Shen is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Hash function & Computer science. The author has an hindex of 44, co-authored 221 publications receiving 8028 citations. Previous affiliations of Fumin Shen include University of Adelaide & Nanjing University of Science and Technology.
Papers
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Journal ArticleDOI
Sequential Discrete Hashing for Scalable Cross-Modality Similarity Retrieval
TL;DR: This paper introduces a novel supervised cross-modality hashing framework, which can generate unified binary codes for instances represented in different modalities and significantly outperforms the state-of-the-art multimodality hashing techniques.
Journal ArticleDOI
Discrete Nonnegative Spectral Clustering
TL;DR: A novel spectral clustering scheme is proposed which deeply explores cluster label properties, including discreteness, nonnegativity, and discrimination, as well as learns robust out-of-sample prediction functions and preserves the natural nonnegative characteristic of the clustering labels.
Proceedings ArticleDOI
Auto-Encoding Twin-Bottleneck Hashing
TL;DR: This paper proposes an efficient and adaptive code-driven graph, which is updated by decoding in the context of an auto-encoder, and introduces into the framework twin bottlenecks that exchange crucial information collaboratively.
Proceedings ArticleDOI
Make a Face: Towards Arbitrary High Fidelity Face Manipulation
TL;DR: This work proposes Additive Focal Variational Auto-encoder (AF-VAE), a novel approach that can arbitrarily manipulate high-resolution face images using a simple yet effective model and only weak supervision of reconstruction and KL divergence losses.
Journal ArticleDOI
A Survey of Human Action Analysis in HRI Applications
TL;DR: This work reviews the existing HRI related references involving the action recognition, prediction, and the robot imitation of the human action, and gives a summary of robot platforms and action datasets that are frequently used in the study of HRI.