no code implementations • 22 Apr 2024 • Ming Liu, Ran Liu, Ye Zhu, Hua Wang, Youyang Qu, Rongsheng Li, Yongpan Sheng, Wray Buntine
ChatGPT has changed the AI community and an active research line is the performance evaluation of ChatGPT.
no code implementations • 6 Apr 2024 • Yongqi Yang, Zhihao Qian, Ye Zhu, Yu Wu
The boom of Generative AI brings opportunities entangled with risks and concerns.
no code implementations • 16 Mar 2024 • Yang Cao, Haolong Xiang, Hang Zhang, Ye Zhu, Kai Ming Ting
Anomaly detection is a longstanding and active research area that has many applications in domains such as finance, security, and manufacturing.
no code implementations • 16 Dec 2023 • Sai Wang, Ye Zhu, Ruoyu Wang, Amaya Dharmasiri, Olga Russakovsky, Yu Wu
While face swapping and attribute editing are performed on similar face regions such as eyes and nose, the inpainting operation can be performed on random image regions, removing the spurious correlations of previous datasets.
no code implementations • 13 Oct 2023 • Ye Zhu, Yu Wu, Zhiwei Deng, Olga Russakovsky, Yan Yan
While the current trend in the generative field is scaling up towards larger models and more training data for generalized domain representations, we go the opposite direction in this work by synthesizing unseen domain images without additional training.
no code implementations • 8 Oct 2023 • Zi Jing Wang, Ye Zhu, Kai Ming Ting
Independent of the distance measure employed, existing clustering algorithms have another challenge: either effectiveness issues or high time complexity.
1 code implementation • 14 Jun 2023 • Ruoyu Wang, Yongqi Yang, Zhihao Qian, Ye Zhu, Yu Wu
In this work, we investigate the diffusion (physics) in diffusion (machine learning) properties and propose our Cyclic One-Way Diffusion (COW) method to control the direction of diffusion phenomenon given a pre-trained frozen diffusion model for versatile customization application scenarios, where the low-level pixel information from the conditioning needs to be preserved.
no code implementations • 2 May 2023 • Chen Li, Yang Cao, Ye Zhu, Debo Cheng, Chengyuan Li, Yasuhiko Morimoto
Using knowledge graphs to assist deep learning models in making recommendation decisions has recently been proven to effectively improve the model's interpretability and accuracy.
1 code implementation • 4 Apr 2023 • Duo Xu, Jonathan C. Tan, Chia-Jung Hsu, Ye Zhu
We introduce the state-of-the-art deep learning Denoising Diffusion Probabilistic Model (DDPM) as a method to infer the volume or number density of giant molecular clouds (GMCs) from projected mass surface density maps.
2 code implementations • 24 Mar 2023 • Ye Zhu, Jie Yang, Si-Qi Liu, Ruimao Zhang
Semi-supervised medical image segmentation has attracted much attention in recent years because of the high cost of medical image annotations.
2 code implementations • 30 Dec 2022 • Yang Cao, Ye Zhu, Kai Ming Ting, Flora D. Salim, Hong Xian Li, Luxing Yang, Gang Li
Detecting abrupt changes in data distribution is one of the most significant tasks in streaming data analysis.
no code implementations • 19 Oct 2022 • Yingchun Guo, Huan He, Ye Zhu, Yang Yu
Domain generalization person re-identification (DG Re-ID) aims to directly deploy a model trained on the source domain to the unseen target domain with good generalization, which is a challenging problem and has practical value in a real-world deployment.
1 code implementation • 11 Oct 2022 • Xiangguang Chen, Ye Zhu, Yu Li, Bingtao Fu, Lei Sun, Ying Shan, Shan Liu
Unlike previous works, our framework is data efficient, which requires a small amount of matting ground-truth to learn to estimate high quality object mattes.
no code implementations • 5 Oct 2022 • Ye Zhu, Yu Wu, Nicu Sebe, Yan Yan
We are perceiving and communicating with the world in a multisensory manner, where different information sources are sophisticatedly processed and interpreted by separate parts of the human brain to constitute a complex, yet harmonious and unified sensing system.
1 code implementation • 23 Jun 2022 • Weijie Ma, Ye Zhu, Ruimao Zhang, Jie Yang, Yiwen Hu, Zhen Li, Li Xiang
By aligning the class tokens and spatial attention maps of paired NBI and WL images at different levels, the Transformer achieves the ability to keep both global and local representation consistency for the above two modalities.
no code implementations • 21 Jun 2022 • Jie Yang, Ye Zhu, Chaoqun Wang, Zhen Li, Ruimao Zhang
Integrating multi-modal data to promote medical image analysis has recently gained great attention.
1 code implementation • 16 Jun 2022 • Yuanfeng Ji, Haotian Bai, Jie Yang, Chongjian Ge, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, Ping Luo
Constraint by the high cost of collecting and labeling 3D medical data, most of the deep learning models to date are driven by datasets with a limited number of organs of interest or samples, which still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of various methods.
1 code implementation • 15 Jun 2022 • Ye Zhu, Yu Wu, Kyle Olszewski, Jian Ren, Sergey Tulyakov, Yan Yan
Diffusion probabilistic models (DPMs) have become a popular approach to conditional generation, due to their promising results and support for cross-modal synthesis.
1 code implementation • 23 Apr 2022 • Zhenghao Zhao, Ye Zhu, Xiaoguang Zhu, Yuzhang Shang, Yan Yan
Most current AI systems rely on the premise that the input visual data are sufficient to achieve competitive performance in various computer vision tasks.
1 code implementation • 1 Apr 2022 • Ye Zhu, Kyle Olszewski, Yu Wu, Panos Achlioptas, Menglei Chai, Yan Yan, Sergey Tulyakov
We present Dance2Music-GAN (D2M-GAN), a novel adversarial multi-modal framework that generates complex musical samples conditioned on dance videos.
no code implementations • 23 Feb 2022 • Xiaoguang Zhu, Ye Zhu, Haoyu Wang, Honglin Wen, Yan Yan, Peilin Liu
To solve the problem, we propose a multi-modality feature fusion network to combine the modalities of the skeleton sequence and RGB frame instead of the RGB video, as the key information contained by the combination of skeleton sequence and RGB frame is close to that of the skeleton sequence and RGB video.
no code implementations • 29 Sep 2021 • Kai Ming Ting, Takashi Washio, Ye Zhu, Yang Xu
The curse of dimensionality has been studied in different aspects.
1 code implementation • 26 Jun 2021 • Ye Zhu, Yu Wu, Yi Yang, Yan Yan
Current vision and language tasks usually take complete visual data (e. g., raw images or videos) as input, however, practical scenarios may often consist the situations where part of the visual information becomes inaccessible due to various reasons e. g., restricted view with fixed camera or intentional vision block for security concerns.
no code implementations • 4 Jun 2021 • Jafar Pourbemany, Almabrok Essa, Ye Zhu
The proposed method is based on measuring fluctuations in the Hue, and can therefore extract both HR and RR from the video of a user's face.
no code implementations • 5 Feb 2021 • Ye Zhu, Yu Wu, Hugo Latapie, Yi Yang, Yan Yan
People can easily imagine the potential sound while seeing an event.
no code implementations • 12 Oct 2020 • Xin Han, Ye Zhu, Kai Ming Ting, Gang Li
In this paper, we identify the root cause of this issue and show that the use of a data-dependent kernel (instead of distance or existing kernel) provides an effective means to address it.
no code implementations • 18 Aug 2020 • Ye Zhu, Yan Yan, Oleg Komogortsev
In this work, we tackle the problem of ternary eye movement classification, which aims to separate fixations, saccades and smooth pursuits from the raw eye positional data.
1 code implementation • ECCV 2020 • Ye Zhu, Yu Wu, Yi Yang, Yan Yan
With the arising concerns for the AI systems provided with direct access to abundant sensitive information, researchers seek to develop more reliable AI with implicit information sources.
no code implementations • 21 Feb 2020 • Yuan Jin, He Zhao, Ming Liu, Ye Zhu, Lan Du, Longxiang Gao, He Zhang, Yunfeng Li
Based on the ELBOs, we propose a VAE-based Bayesian MF framework.
1 code implementation • 14 Feb 2020 • Kai Ming Ting, Jonathan R. Wells, Ye Zhu
This paper introduces a new similarity measure called point-set kernel which computes the similarity between an object and a set of objects.
1 code implementation • 30 Jun 2019 • Xiaoyu Qin, Kai Ming Ting, Ye Zhu, Vincent CS Lee
A new type of clusters called mass-connected clusters is formally defined.
1 code implementation • 24 Jun 2019 • Ye Zhu, Kai Ming Ting
This paper presents a new insight into improving the performance of Stochastic Neighbour Embedding (t-SNE) by using Isolation kernel instead of Gaussian kernel.
no code implementations • 3 May 2019 • Xiong Deng, Chao Chen, Deyang Chen, Xiangbin Cai, Xiaozhe Yin, Chao Xu, Fei Sun, Caiwen Li, Yan Li, Han Xu, Mao Ye, Guo Tian, Zhen Fan, Zhipeng Hou, Minghui Qin, Yu Chen, Zhenlin Luo, Xubing Lu, Guofu Zhou, Lang Chen, Ning Wang, Ye Zhu, Xingsen Gao, Jun-Ming Liu
The limitation of commercially available single-crystal substrates and the lack of continuous strain tunability preclude the ability to take full advantage of strain engineering for further exploring novel properties and exhaustively studying fundamental physics in complex oxides.
Materials Science
no code implementations • 5 Dec 2018 • Yuan Jin, Mark Carman, Ye Zhu, Yong Xiang
Our survey is the first to bridge the two branches by providing technical details on how they work together under frameworks that systematically unify crowdsourcing aspects modelled by both of them to determine the response quality.
no code implementations • 30 Nov 2018 • Ye Zhu, Sven Ewan Shepstone, Pablo Martínez-Nuevo, Miklas Strøm Kristoffersen, Fabien Moutarde, Zhuang Fu
Deep learning within the context of point clouds has gained much research interest in recent years mostly due to the promising results that have been achieved on a number of challenging benchmarks, such as 3D shape recognition and scene semantic segmentation.
1 code implementation • 8 Oct 2018 • Ye Zhu, Kai Ming Ting, Yuan Jin, Maia Angelova
This paper focuses on density-based clustering, particularly the Density Peak (DP) algorithm and the one based on density-connectivity DBSCAN; and proposes a new method which takes advantage of the individual strengths of these two methods to yield a density-based hierarchical clustering algorithm.
1 code implementation • 5 Oct 2018 • Ye Zhu, Kai Ming Ting, Mark Carman, Maia Angelova
To match the implicit assumption, we propose to transform a given dataset such that the transformed clusters have approximately the same density while all regions of locally low density become globally low density -- homogenising cluster density while preserving the cluster structure of the dataset.
no code implementations • 12 Feb 2018 • Yuan Jin, Mark Carman, Ye Zhu, Wray Buntine
Experiments show that our model(1) improves the performance of both quality control for crowd-sourced answers and next answer prediction for crowd-workers, and (2) can potentially provide coherent rankings of questions in terms of their difficulty and subjectivity, so that task providers can refine their designs of the crowdsourcing tasks, e. g. by removing highly subjective questions or inappropriately difficult questions.