no code implementations • 15 Jul 2023 • Zhihui Li, Francesco Montomoli, Sanjiv Sharma
The performance of PINNs is assessed here by solving both the forward and inverse problems.
no code implementations • 22 May 2023 • De Cheng, Xiaojian Huang, Nannan Wang, Lingfeng He, Zhihui Li, Xinbo Gao
Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims at learning modality-invariant features from unlabeled cross-modality dataset, which is crucial for practical applications in video surveillance systems.
1 code implementation • 21 Feb 2023 • Hu Gao, Zhihui Li, Depeng Dang, Ning Wang, Jingfan Yang
In this way, the feature loss and the complexity of the model is reduced, and the degradation of deep neural network during training is avoided.
1 code implementation • 21 Feb 2023 • Hu Gao, Zhihui Li, Depeng Dang, Jingfan Yang, Ning Wang
Then, we compare the prediction accuracy of the three models.
no code implementations • ICCV 2023 • Mingfei Han, Yali Wang, Zhihui Li, Lina Yao, Xiaojun Chang, Yu Qiao
To tackle this problem, we propose a concise Hybrid Temporal-scale Multimodal Learning (HTML) framework, which can effectively align lingual and visual features to discover core object semantics in the video, by learning multimodal interaction hierarchically from different temporal scales.
Ranked #6 on Referring Video Object Segmentation on Refer-YouTube-VOS (using extra training data)
1 code implementation • 11 Oct 2022 • Siyi Hu, Yifan Zhong, Minquan Gao, Weixun Wang, Hao Dong, Xiaodan Liang, Zhihui Li, Xiaojun Chang, Yaodong Yang
A significant challenge facing researchers in the area of multi-agent reinforcement learning (MARL) pertains to the identification of a library that can offer fast and compatible development for multi-agent tasks and algorithm combinations, while obviating the need to consider compatibility issues.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 21 Sep 2021 • Changlin Li, Guangrun Wang, Bing Wang, Xiaodan Liang, Zhihui Li, Xiaojun Chang
Dynamic networks have shown their promising capability in reducing theoretical computation complexity by adapting their architectures to the input during inference.
no code implementations • CVPR 2021 • Zhihui Li, Lina Yao
Temporal action detection on unconstrained videos has seen significant research progress in recent years.
1 code implementation • CVPR 2021 • Changlin Li, Guangrun Wang, Bing Wang, Xiaodan Liang, Zhihui Li, Xiaojun Chang
Here, we explore a dynamic network slimming regime, named Dynamic Slimmable Network (DS-Net), which aims to achieve good hardware-efficiency via dynamically adjusting filter numbers of networks at test time with respect to different inputs, while keeping filters stored statically and contiguously in hardware to prevent the extra burden.
no code implementations • 17 Mar 2021 • Xiaojun Chang, Pengzhen Ren, Pengfei Xu, Zhihui Li, Xiaojiang Chen, Alex Hauptmann
For example, given an image, we want to not only detect and recognize objects in the image, but also know the relationship between objects (visual relationship detection), and generate a text description (image captioning) based on the image content.
no code implementations • 17 Mar 2021 • Pengzhen Ren, Gang Xiao, Xiaojun Chang, Yun Xiao, Zhihui Li, Xiaojiang Chen
Accordingly, because of the automated design of its network structure, Neural architecture search (NAS) has achieved great success in the image processing field and attracted substantial research attention in recent years.
no code implementations • 24 Sep 2020 • Caixia Yan, Xiaojun Chang, Minnan Luo, Qinghua Zheng, Xiaoqin Zhang, Zhihui Li, Feiping Nie
In this regard, a novel self-weighted robust LDA with l21-norm based pairwise between-class distance criterion, called SWRLDA, is proposed for multi-class classification especially with edge classes.
1 code implementation • 30 Aug 2020 • Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Brij B. Gupta, Xiaojiang Chen, Xin Wang
Therefore, deep active learning (DAL) has emerged.
no code implementations • 1 Jun 2020 • Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Xiaojiang Chen, Xin Wang
Neural Architecture Search (NAS) is just such a revolutionary algorithm, and the related research work is complicated and rich.
no code implementations • 25 Apr 2019 • Lei Zhu, Zi Huang, Zhihui Li, Liang Xie, Heng Tao Shen
To address the problem, in this paper, we propose a novel hashing approach, dubbed as \emph{Discrete Semantic Transfer Hashing} (DSTH).
no code implementations • 25 Jul 2017 • De Cheng, Yihong Gong, Zhihui Li, Weiwei Shi, Alexander G. Hauptmann, Nanning Zheng
The proposed method can take full advantages of the structured distance relationships among these training samples, with the constructed complete graph.
no code implementations • 4 Feb 2017 • Minnan Luo, Xiaojun Chang, Zhihui Li, Liqiang Nie, Alexander G. Hauptmann, Qinghua Zheng
The heterogeneity-gap between different modalities brings a significant challenge to multimedia information retrieval.