no code implementations • COLING 2022 • Siyu Wang, Jianhui Jiang, Yao Huang, Yin Wang
However, we observed that most of the keyphrases are composed of some important words (seed words) in the source text, and if these words can be identified accurately and copied to create more keyphrases, the performance of the model might be improved.
2 code implementations • 9 Mar 2024 • Hao Lu, Xuesong Niu, Jiyao Wang, Yin Wang, Qingyong Hu, Jiaqi Tang, Yuting Zhang, Kaishen Yuan, Bin Huang, Zitong Yu, Dengbo He, Shuiguang Deng, Hao Chen, Yingcong Chen, Shiguang Shan
In conclusion, this paper provides valuable insights into the potential applications and challenges of MLLMs in human-centric computing.
no code implementations • 14 Sep 2023 • Shiqiao Meng, Zonglin Di, Siwei Yang, Yin Wang
Our extensive experimental results show that the prediction accuracy increases with the amount of the weakly labeled data, as well as the road density in the areas chosen for training.
no code implementations • ICCV 2023 • Yin Wang, Zhiying Leng, Frederick W. B. Li, Shun-Cheng Wu, Xiaohui Liang
Text-driven human motion generation in computer vision is both significant and challenging.
Ranked #13 on Motion Synthesis on KIT Motion-Language
no code implementations • ICCV 2023 • Zhiying Leng, Shun-Cheng Wu, Mahdi Saleh, Antonio Montanaro, Hao Yu, Yin Wang, Nassir Navab, Xiaohui Liang, Federico Tombari
In this work, we propose the first precise hand-object reconstruction method in hyperbolic space, namely Dynamic Hyperbolic Attention Network (DHANet), which leverages intrinsic properties of hyperbolic space to learn representative features.
1 code implementation • ICCV 2023 • Yifan Yang, Weiquan Huang, Yixuan Wei, Houwen Peng, Xinyang Jiang, Huiqiang Jiang, Fangyun Wei, Yin Wang, Han Hu, Lili Qiu, Yuqing Yang
To address this issue, we propose an attentive token removal approach for CLIP training, which retains tokens with a high semantic correlation to the text description.
1 code implementation • 28 Jul 2022 • Tianqi Guo, Yin Wang, Luis Solorio, Jan P. Allebach
We share our recent findings in an attempt to train a universal segmentation network for various cell types and imaging modalities.
no code implementations • 2 Mar 2022 • Qingsong Zhao, Yi Wang, Shuguang Dou, Chen Gong, Yin Wang, Cairong Zhao
Regarding this hypothesis, we propose a novel regularization to improve discriminative learning.
no code implementations • 8 Nov 2021 • Eduardo Conde-Sousa, João Vale, Ming Feng, Kele Xu, Yin Wang, Vincenzo Della Mea, David La Barbera, Ehsan Montahaei, Mahdieh Soleymani Baghshah, Andreas Turzynski, Jacob Gildenblat, Eldad Klaiman, Yiyu Hong, Guilherme Aresta, Teresa Araújo, Paulo Aguiar, Catarina Eloy, António Polónia
Breast cancer is the most common malignancy in women, being responsible for more than half a million deaths every year.
1 code implementation • 6 Jun 2021 • Siwei Yang, Shaozuo Yu, Bingchen Zhao, Yin Wang
Visual pattern recognition over agricultural areas is an important application of aerial image processing.
no code implementations • 17 May 2021 • Weiquan Huang, Yan Bai, Qiuyu Ren, Xinbo Zhao, Ming Feng, Yin Wang
In particular, most existing unsupervised and domain adaptation ReID methods utilize only the public datasets in their experiments, with labels removed.
no code implementations • 11 Jan 2021 • Yuqi Liu, Yin Wang, Haikuan Du, Shen Cai
To this end, the proposed method first uses local structured sampling methods such as HEALPix to construct a transformer grid by using the information of spherical points and its adjacent points, and then transforms the spherical signals to the vectors through the grid.
1 code implementation • ECCV 2020 • Yuexi Zhang, Yin Wang, Octavia Camps, Mario Sznaier
Human pose estimation in video relies on local information by either estimating each frame independently or tracking poses across frames.
1 code implementation • 21 Apr 2020 • Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer Hobbs, Naira Hovakimyan, Thomas S. Huang, Honghui Shi, Yunchao Wei, Zilong Huang, Alexander Schwing, Robert Brunner, Ivan Dozier, Wyatt Dozier, Karen Ghandilyan, David Wilson, Hyunseong Park, Junhee Kim, Sungho Kim, Qinghui Liu, Michael C. Kampffmeyer, Robert Jenssen, Arnt B. Salberg, Alexandre Barbosa, Rodrigo Trevisan, Bingchen Zhao, Shaozuo Yu, Siwei Yang, Yin Wang, Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Ng, Van Thong Huynh, Soo-Hyung Kim, In-Seop Na, Ujjwal Baid, Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay Talbar, Jianyu Tang
The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially for the semantic segmentation task associated with our challenge dataset.
1 code implementation • NeurIPS 2020 • Hui Chen, Fangqing Liu, Yin Wang, Liyue Zhao, Hao Wu
Learning binary classifiers only from positive and unlabeled (PU) data is an important and challenging task in many real-world applications, including web text classification, disease gene identification and fraud detection, where negative samples are difficult to verify experimentally.
no code implementations • CVPR 2019 • Tao Sun, Zonglin Di, Pengyu Che, Chun Liu, Yin Wang
Deep learning is revolutionizing the mapping industry.
no code implementations • CVPR 2016 • Yongfang Cheng, Yin Wang, Mario Sznaier, Octavia Camps
This paper considers the problem of recovering a subspace arrangement from noisy samples, potentially corrupted with outliers.
no code implementations • CVPR 2016 • Xikang Zhang, Yin Wang, Mengran Gou, Mario Sznaier, Octavia Camps
In this paper we propose a new framework to compare and classify temporal sequences.
no code implementations • CVPR 2015 • Yin Wang, Caglayan Dicle, Mario Sznaier, Octavia Camps
Linear Robust Regression (LRR) seeks to find the parameters of a linear mapping from noisy data corrupted from outliers, such that the number of inliers (i. e. pairs of points where the fitting error of the model is less than a given bound) is maximized.
no code implementations • 23 Jan 2015 • Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen
With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet.