1 code implementation • 26 Nov 2023 • Yixuan Zhou, Yi Qu, Xing Xu, Fumin Shen, Jingkuan Song, HengTao Shen
In the proposed BN-WVAD, we leverage the Divergence of Feature from Mean vector (DFM) of BatchNorm as a reliable abnormality criterion to discern potential abnormal snippets in abnormal videos.
Anomaly Detection In Surveillance Videos Video Anomaly Detection
1 code implementation • 12 Oct 2023 • Yixuan Zhou, Xuanhan Wang, Xing Xu, Lei Zhao, Jingkuan Song
Inspired by this observation, we introduce a lightweight and powerful alternative, Spatially Unidimensional Self-Attention (SUSA), to the pointwise (1x1) convolution that is the main computational bottleneck in the depthwise separable 3c3 convolution.
no code implementations • 31 Aug 2023 • Weiqin Li, Shun Lei, Qiaochu Huang, Yixuan Zhou, Zhiyong Wu, Shiyin Kang, Helen Meng
The spontaneous behavior that often occurs in conversations makes speech more human-like compared to reading-style.
1 code implementation • 29 Aug 2023 • Yixuan Zhou, Xing Xu, Jingkuan Song, Fumin Shen, Heng Tao Shen
Unsupervised anomaly detection (UAD) attracts a lot of research interest and drives widespread applications, where only anomaly-free samples are available for training.
Ranked #5 on Anomaly Detection on MVTec AD
1 code implementation • ICCV 2023 • Yixuan Zhou, Yi Qu, Xing Xu, HengTao Shen
To overcome this bottleneck, we leverage class priors to restrict the generalization scope of the class-agnostic SAM and propose a class-aware smoothness optimization algorithm named Imbalanced-SAM (ImbSAM).
Semi-supervised Anomaly Detection Supervised Anomaly Detection
1 code implementation • 30 May 2023 • Yixuan Zhou, Peiyu Yang, Yi Qu, Xing Xu, Zhe Sun, Andrzej Cichocki
Unlike existing SSAD methods that resort to strict loss supervision, AnoOnly suspends it and introduces a form of weak supervision for normal data.
Semi-supervised Anomaly Detection Supervised Anomaly Detection +1
1 code implementation • 21 Jun 2022 • Xuanhan Wang, Lianli Gao, Yixuan Zhou, Jingkuan Song, Meng Wang
Human densepose estimation, aiming at establishing dense correspondences between 2D pixels of human body and 3D human body template, is a key technique in enabling machines to have an understanding of people in images.
1 code implementation • 31 Mar 2022 • Xueyuan Chen, Changhe Song, Yixuan Zhou, Zhiyong Wu, Changbin Chen, Zhongqin Wu, Helen Meng
In this paper, we propose a span-based Mandarin prosodic structure prediction model to obtain an optimal prosodic structure tree, which can be converted to corresponding prosodic label sequence.
no code implementations • 23 Mar 2022 • Shun Lei, Yixuan Zhou, Liyang Chen, Zhiyong Wu, Shiyin Kang, Helen Meng
In this paper, we propose a hierarchical framework to model speaking style from context.
2 code implementations • 26 Jan 2022 • Jinjie Zhang, Yixuan Zhou, Rayan Saab
Additionally, our error analysis expands the results of previous work on GPFQ to handle general quantization alphabets, showing that for quantizing a single-layer network, the relative square error essentially decays linearly in the number of weights -- i. e., level of over-parametrization.
no code implementations • 14 Apr 2021 • Yixuan Zhou, Changhe Song, Jingbei Li, Zhiyong Wu, Yanyao Bian, Dan Su, Helen Meng
Exploiting rich linguistic information in raw text is crucial for expressive text-to-speech (TTS).
no code implementations • 13 Dec 2020 • Changhe Song, Jingbei Li, Yixuan Zhou, Zhiyong Wu, Helen Meng
Meanwhile, nuclear-norm maximization loss is introduced to enhance the discriminability and diversity of the embeddings of constituent labels.