1 code implementation • 28 Mar 2022 • Yu Du, Fangyun Wei, Zihe Zhang, Miaojing Shi, Yue Gao, Guoqi Li
In this paper, we introduce a novel method, detection prompt (DetPro), to learn continuous prompt representations for open-vocabulary object detection based on the pre-trained vision-language model.
no code implementations • 12 Mar 2022 • Fuhai Chen, Rongrong Ji, Chengpeng Dai, Xuri Ge, Shengchuang Zhang, Xiaojing Ma, Yue Gao
Echocardiography is widely used to clinical practice for diagnosis and treatment, e. g., on the common congenital heart defects.
no code implementations • 17 Oct 2021 • Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Xinghao Ding, Yongjian Wu, Feiyue Huang, Yue Gao, Rongrong Ji
Based on the LaConv module, we further build the first fully language-driven convolution network, termed as LaConvNet, which can unify the visual recognition and multi-modal reasoning in one forward structure.
no code implementations • ICLR 2022 • Yutong Feng, Jianwen Jiang, Mingqian Tang, Rong Jin, Yue Gao
Though for most cases, the pre-training stage is conducted based on supervised methods, recent works on self-supervised pre-training have shown powerful transferability and even outperform supervised pre-training on multiple downstream tasks.
no code implementations • 29 Sep 2021 • Xueqi Ma, Yubo Zhang, Weifeng Liu, Yue Gao
Based on the frequency principle on GNNs, we present a novel powerful GNNs framework, Multi-Scale Frequency Enhanced Graph Neural Networks (MSF-GNNs) which considers multi-scale representations from wavelet decomposition.
no code implementations • 29 Sep 2021 • Xueqi Ma, Pan Li, Qiong Cao, James Bailey, Yue Gao
In FAHGNN, we explore the influence of node features for the expressive power of GNNs and augment features by introducing common features and personal features to model information.
no code implementations • 16 Jul 2021 • Yue Gao, Kry Yik Chau Lui, Pablo Hernandez-Leal
Trading markets represent a real-world financial application to deploy reinforcement learning agents, however, they carry hard fundamental challenges such as high variance and costly exploration.
no code implementations • 28 Jun 2021 • Yue Gao, Garvesh Raskutti
Network estimation from multi-variate point process or time series data is a problem of fundamental importance.
no code implementations • 15 Jun 2021 • Yutong Feng, Jianwen Jiang, Ziyuan Huang, Zhiwu Qing, Xiang Wang, Shiwei Zhang, Mingqian Tang, Yue Gao
This paper presents our solution to the AVA-Kinetics Crossover Challenge of ActivityNet workshop at CVPR 2021.
Ranked #1 on
Spatio-Temporal Action Localization
on AVA-Kinetics
(using extra training data)
1 code implementation • 8 Jun 2021 • Yang Hu, Haoxuan You, Zhecan Wang, Zhicheng Wang, Erjin Zhou, Yue Gao
Graph Neural Network (GNN) has been demonstrated its effectiveness in dealing with non-Euclidean structural data.
1 code implementation • NeurIPS 2021 • Fangyun Wei, Yue Gao, Zhirong Wu, Han Hu, Stephen Lin
Image-level contrastive representation learning has proven to be highly effective as a generic model for transfer learning.
no code implementations • 13 May 2021 • Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Classical global convergence results for first-order methods rely on uniform smoothness and the \L{}ojasiewicz inequality.
no code implementations • 18 Apr 2021 • Yue Gao, Ilia Shumailov, Kassem Fawaz
As real-world images come in varying sizes, the machine learning model is part of a larger system that includes an upstream image scaling algorithm.
no code implementations • CVPR 2021 • Xuancheng Zhang, Yutong Feng, Siqi Li, Changqing Zou, Hai Wan, Xibin Zhao, Yandong Guo, Yue Gao
This paper presents a view-guided solution for the task of point cloud completion.
no code implementations • CVPR 2021 • Yue Gao, Fangyun Wei, Jianmin Bao, Shuyang Gu, Dong Chen, Fang Wen, Zhouhui Lian
However, we observe that the generator tends to find a tricky way to hide information from the original image to satisfy the constraint of cycle consistency, making it impossible to maintain the rich details (e. g., wrinkles and moles) of non-editing areas.
1 code implementation • ICCV 2021 • Zihan Xu, Mingbao Lin, Jianzhuang Liu, Jie Chen, Ling Shao, Yue Gao, Yonghong Tian, Rongrong Ji
We prove that reviving the "dead weights" by ReCU can result in a smaller quantization error.
no code implementations • 1 Jan 2021 • Yutong Feng, Jianwen Jiang, Yue Gao
To tackle this problem, we introduce incremental graph learning (IGL), a general framework to formulate the learning on growing graphs in an incremental manner, where traditional graph learning method could be deployed as a basic model.
no code implementations • ICCV 2021 • Siqi Li, Yutong Feng, Yipeng Li, Yu Jiang, Changqing Zou, Yue Gao
Therefore, it is imperative to explore the algorithm of event stream super-resolution, which is a non-trivial task due to the sparsity and strong spatio-temporal correlation of the events from an event camera.
no code implementations • 13 Dec 2020 • Jiayi Ji, Yunpeng Luo, Xiaoshuai Sun, Fuhai Chen, Gen Luo, Yongjian Wu, Yue Gao, Rongrong Ji
The latter contains a Global Adaptive Controller that can adaptively fuse the global information into the decoder to guide the caption generation.
2 code implementations • CVPR 2021 • He Wang, Yezhen Cong, Or Litany, Yue Gao, Leonidas J. Guibas
On KITTI, we are the first to demonstrate semi-supervised 3D object detection and our method surpasses a fully supervised baseline from 1. 8% to 7. 6% under different label ratios and categories.
1 code implementation • 27 Nov 2020 • Haoyi Fan, Fengbin Zhang, Yue Gao
In this paper, we present SelfTime: a general self-supervised time series representation learning framework, by exploring the inter-sample relation and intra-temporal relation of time series to learn the underlying structure feature on the unlabeled time series.
2 code implementations • 16 May 2020 • Yizhi Wang, Yue Gao, Zhouhui Lian
To the best of our knowledge, our model is the first one in the literature which is capable of generating glyph images in new font styles, instead of retrieving existing fonts, according to given values of specified font attributes.
no code implementations • 7 May 2020 • Donglin Di, Feng Shi, Fuhua Yan, Liming Xia, Zhanhao Mo, Zhongxiang Ding, Fei Shan, Shengrui Li, Ying WEI, Ying Shao, Miaofei Han, Yaozong Gao, He Sui, Yue Gao, Dinggang Shen
The main challenge in early screening is how to model the confusing cases in the COVID-19 and CAP groups, with very similar clinical manifestations and imaging features.
no code implementations • 5 Apr 2020 • Xiaolan Liu, Jiadong Yu, Yue Gao
To support popular Internet of Things (IoT) applications such as virtual reality, mobile games and wearable devices, edge computing provides a front-end distributed computing archetype of centralized cloud computing with low latency.
no code implementations • 31 Mar 2020 • Siqi Li, Changqing Zou, Yipeng Li, Xibin Zhao, Yue Gao
This paper presents an end-to-end 3D convolutional network named attention-based multi-modal fusion network (AMFNet) for the semantic scene completion (SSC) task of inferring the occupancy and semantic labels of a volumetric 3D scene from single-view RGB-D images.
no code implementations • 3 Mar 2020 • Yue Gao, Harrison Rosenberg, Kassem Fawaz, Somesh Jha, Justin Hsu
In test-time attacks an adversary crafts adversarial examples, which are specially crafted perturbations imperceptible to humans which, when added to an input example, force a machine learning model to misclassify the given input example.
no code implementations • 1 Feb 2020 • Chenggang Yan, Biao Gong, Yuxuan Wei, Yue Gao
Therefore, we try to introduce the multi-view deep neural network into the hash learning field, and design an efficient and innovative retrieval model, which has achieved a significant improvement in retrieval performance.
3 code implementations • 11 Oct 2019 • Yue Gao, Yuan Guo, Zhouhui Lian, Yingmin Tang, Jianguo Xiao
Extensive experiments on both English and Chinese artistic glyph image datasets demonstrate the superiority of our model in generating high-quality stylized glyph images against other state-of-the-art methods.
Ranked #1 on
Glyph Image Generation
on English Glyph
1 code implementation • 1 Jul 2019 • Jianwen Jiang, Yuxuan Wei, Yifan Feng, Jingxuan Cao, Yue Gao
Then hypergraph convolution is introduced to encode high-order data relations in a hypergraph structure.
no code implementations • ICCV 2019 • Jie Li, Rongrong Ji, Hong Liu, Xiaopeng Hong, Yue Gao, Qi Tian
In this paper, we make the first attempt in attacking image retrieval systems.
no code implementations • 2 Dec 2018 • Haoxuan You, Yifan Feng, Xibin Zhao, Changqing Zou, Rongrong Ji, Yue Gao
More specifically, based on the relation score module, the point-single-view fusion feature is first extracted by fusing the point cloud feature and each single view feature with point-singe-view relation, then the point-multi-view fusion feature is extracted by fusing the point cloud feature and the features of different number of views with point-multi-view relation.
2 code implementations • 28 Nov 2018 • Yutong Feng, Yifan Feng, Haoxuan You, Xibin Zhao, Yue Gao
However, there is little effort on using mesh data in recent years, due to the complexity and irregularity of mesh data.
1 code implementation • 25 Sep 2018 • Yifan Feng, Haoxuan You, Zizhao Zhang, Rongrong Ji, Yue Gao
In this paper, we present a hypergraph neural networks (HGNN) framework for data representation learning, which can encode high-order data correlation in a hypergraph structure.
no code implementations • 23 Aug 2018 • Haoxuan You, Yifan Feng, Rongrong Ji, Yue Gao
With the recent proliferation of deep learning, various deep models with different representations have achieved the state-of-the-art performance.
no code implementations • CVPR 2018 • Yifan Feng, Zizhao Zhang, Xibin Zhao, Rongrong Ji, Yue Gao
The proposed GVCNN framework is composed of a hierarchical view-group-shape architecture, i. e., from the view level, the group level and the shape level, which are organized using a grouping strategy.