Search Results - "Yonghong Tian"

Sequential Deep Trajectory Descriptor for Action Recognition With Three-Stream CNN by Shi, Yemin, Tian, Yonghong, Wang, Yaowei, Huang, Tiejun

“…Learning the spatial-temporal representation of motion information is crucial to human action recognition. Nevertheless, most of the existing features or…”
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P-ODN: Prototype-based Open Deep Network for Open Set Recognition by Shu, Yu, Shi, Yemin, Wang, Yaowei, Huang, Tiejun, Tian, Yonghong

“…Most of the existing recognition algorithms are proposed for closed set scenarios, where all categories are known beforehand. However, in practice, recognition…”
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Can We Beat DDoS Attacks in Clouds? by Shui Yu, Yonghong Tian, Song Guo, Wu, Dapeng Oliver

“…Cloud is becoming a dominant computing platform. Naturally, a question that arises is whether we can beat notorious DDoS attacks in a cloud environment…”
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Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks by Fang, Wei, Yu, Zhaofei, Chen, Yanqi, Masquelier, Timothee, Huang, Tiejun, Tian, Yonghong

“…Spiking Neural Networks (SNNs) have attracted enormous research interest due to temporal information processing capability, low power consumption, and high…”
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Deep Relative Distance Learning: Tell the Difference between Similar Vehicles by Liu, Hongye, Tian, Yonghong, Wang, Yaowei, Pang, Lu, Huang, Tiejun

“…The growing explosion in the use of surveillance cameras in public security highlights the importance of vehicle search from a large-scale image or video…”
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Part-guided Relational Transformers for Fine-grained Visual Recognition by Zhao, Yifan, Li, Jia, Chen, Xiaowu, Tian, Yonghong

“…Fine-grained visual recognition is to classify objects with visually similar appearances into subcategories, which has made great progress with the development…”
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Joint Semantic and Latent Attribute Modelling for Cross-Class Transfer Learning by Peng, Peixi, Tian, Yonghong, Xiang, Tao, Wang, Yaowei, Pontil, Massimiliano, Huang, Tiejun

“…A number of vision problems such as zero-shot learning and person re-identification can be considered as cross-class transfer learning problems. As mid-level…”
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Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning by Qiao, Limeng, Shi, Yemin, Li, Jia, Tian, Yonghong, Huang, Tiejun, Wang, Yaowei

“…Few-shot learning, which aims at extracting new concepts rapidly from extremely few examples of novel classes, has been featured into the meta-learning…”
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Unsupervised Cross-Dataset Transfer Learning for Person Re-identification by Peixi Peng, Tao Xiang, Yaowei Wang, Pontil, Massimiliano, Shaogang Gong, Tiejun Huang, Yonghong Tian

“…Most existing person re-identification (Re-ID) approaches follow a supervised learning framework, in which a large number of labelled matching pairs are…”
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Learning Discriminative Subspaces on Random Contrasts for Image Saliency Analysis by Fang, Shu, Li, Jia, Tian, Yonghong, Huang, Tiejun, Chen, Xiaowu

“…In visual saliency estimation, one of the most challenging tasks is to distinguish targets and distractors that share certain visual attributes. With the…”
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Asynchronous Spatio-Temporal Memory Network for Continuous Event-Based Object Detection by Li, Jianing, Li, Jia, Zhu, Lin, Xiang, Xijie, Huang, Tiejun, Tian, Yonghong

“…Event cameras, offering extremely high temporal resolution and high dynamic range, have brought a new perspective to addressing common object detection…”
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Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey by Wang, Xiao, Chen, Guangyao, Qian Guangwu, Gao Pengcheng, Xiao-Yong, Wei, Wang, Yaowei, Tian Yonghong, Gao, Wen

“…With the urgent demand for generalized deep models, many pre-trained big models are proposed, such as bidirectional encoder representations (BERT), vision…”
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Parsing Objects at a Finer Granularity: A Survey by Zhao, Yifan, Li, Jia, Tian Yonghong

“…Fine-grained visual parsing, including fine-grained part segmentation and fine-grained object recognition, has attracted considerable critical attention due to…”
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Exploiting Multi-grain Ranking Constraints for Precisely Searching Visually-similar Vehicles by Ke Yan, Yonghong Tian, Yaowei Wang, Wei Zeng, Tiejun Huang

“…Precise search of visually-similar vehicles poses a great challenge in computer vision, which needs to find exactly the same vehicle among a massive vehicles…”
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Visual Saliency with Statistical Priors by Li, Jia, Tian, Yonghong, Huang, Tiejun

“…Visual saliency is a useful cue to locate the conspicuous image content. To estimate saliency, many approaches have been proposed to detect the unique or rare…”
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YoTube: Searching Action Proposal Via Recurrent and Static Regression Networks by Hongyuan Zhu, Vial, Romain, Shijian Lu, Xi Peng, Huazhu Fu, Yonghong Tian, Xianbin Cao

“…In this paper, we propose YoTube-a novel deep learning framework for generating action proposals in untrimmed videos, where each action proposal corresponds to…”
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Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video by Li, Jia, Tian, Yonghong, Huang, Tiejun, Gao, Wen

“…In this paper, we present a probabilistic multi-task learning approach for visual saliency estimation in video. In our approach, the problem of visual saliency…”
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Optimizing the Hierarchical Prediction and Coding in HEVC for Surveillance and Conference Videos With Background Modeling by Zhang, Xianguo, Tian, Yonghong, Huang, Tiejun, Dong, Siwei, Gao, Wen

“…For the real-time and low-delay video surveillance and teleconferencing applications, the newly video coding standard HEVC can achieve much higher coding…”
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Finding the Secret of Image Saliency in the Frequency Domain by Li, Jia, Duan, Ling-Yu, Chen, Xiaowu, Huang, Tiejun, Tian, Yonghong

“…There are two sides to every story of visual saliency modeling in the frequency domain. On the one hand, image saliency can be effectively estimated by…”
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Rate-Performance-Loss Optimization for Inter-Frame Deep Feature Coding From Videos by Ding, Lin, Tian, Yonghong, Fan, Hongfei, Wang, Yaowei, Huang, Tiejun

“…With the explosion in the use of cameras in mobile phones or video surveillance systems, it is impossible to transmit a large amount of videos captured from a…”
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