no code implementations • 28 Oct 2024 • Jianmina Ma, Jingtian Ji, Yue Gao
Constrained reinforcement learning has achieved promising progress in safety-critical fields where both rewards and constraints are considered.
no code implementations • 15 Oct 2024 • Zihang Song, Xingjian Zhang, Zhe Chen, Rahim Tafazolli, Yue Gao
The system's ability to process signals with a 2 GHz radio frequency bandwidth using only a 400 MHz average sampling rate enables more efficient spectrum monitoring and access in wideband cognitive radios.
1 code implementation • 14 Oct 2024 • Yifan Feng, Chengwu Yang, Xingliang Hou, Shaoyi Du, Shihui Ying, Zongze Wu, Yue Gao
Existing benchmarks like NLGraph and GraphQA evaluate LLMs on graphs by focusing mainly on pairwise relationships, overlooking the high-order correlations found in real-world data.
no code implementations • 13 Oct 2024 • Pengfei Hu, Yuhang Qian, Tianyue Zheng, Ang Li, Zhe Chen, Yue Gao, Xiuzhen Cheng, Jun Luo
Given the wide adoption of multimodal sensors (e. g., camera, lidar, radar) by autonomous vehicles (AVs), deep analytics to fuse their outputs for a robust perception become imperative.
no code implementations • 1 Oct 2024 • Yongyang Tang, Zhe Chen, Ang Li, Tianyue Zheng, Zheng Lin, Jia Xu, Pin Lv, Zhe Sun, Yue Gao
Cardiovascular disease (CVD) is the leading cause of death and premature mortality worldwide, with occupational environments significantly influencing CVD risk, underscoring the need for effective cardiac monitoring and early warning systems.
no code implementations • 29 Sep 2024 • Yiming Zhao, Dewen Guo, Zhouhui Lian, Yue Gao, Jianhong Han, Jie Feng, Guoping Wang, Bingfeng Zhou, Sheng Li
To bridge the gap between artists and non-specialists, we present a unified framework, Neural-Polyptych, to facilitate the creation of expansive, high-resolution paintings by seamlessly incorporating interactive hand-drawn sketches with fragments from original paintings.
no code implementations • 20 Sep 2024 • Yuxin Zhang, Zheng Lin, Zhe Chen, Zihan Fang, Wenjun Zhu, Xianhao Chen, Jin Zhao, Yue Gao
Despite this potential, the limited satellite-ground communication bandwidth and the heterogeneous operating environments of ground devices-including variations in data, bandwidth, and computing power-pose substantial challenges for effective and robust satellite-assisted FL.
1 code implementation • 9 Aug 2024 • Yifan Feng, Jiangang Huang, Shaoyi Du, Shihui Ying, Jun-Hai Yong, Yipeng Li, Guiguang Ding, Rongrong Ji, Yue Gao
We introduce Hyper-YOLO, a new object detection method that integrates hypergraph computations to capture the complex high-order correlations among visual features.
no code implementations • 1 Jul 2024 • Zheng Lin, Xuanjie Hu, Yuxin Zhang, Zhe Chen, Zihan Fang, Xianhao Chen, Ang Li, Praneeth Vepakomma, Yue Gao
To address this issue, split learning (SL) has emerged as a promising solution by offloading the primary training workload to a server via model partitioning while exchanging activation/activation's gradients with smaller data sizes rather than the entire LLM.
1 code implementation • 20 Jun 2024 • Xuanyu Tian, Zhuoya Dong, Xiyue Lin, Yue Gao, Hongjiang Wei, Yanhang Ma, Jingyi Yu, Yuyao Zhang
Noise2SR trains the network with paired noisy images of different resolutions, which is conducted via SR strategy.
no code implementations • 24 May 2024 • Haoxuan Yuan, Zhe Chen, Zheng Lin, Jinbo Peng, Zihan Fang, Yuhang Zhong, Zihang Song, Yue Gao
To address the above challenges, we first establish connections between the satellites by modeling their sensing data as a graph and devising a graph neural network-based algorithm to achieve effective spectrum sensing.
no code implementations • 9 Apr 2024 • Zihan Fang, Zheng Lin, Zhe Chen, Xianhao Chen, Yue Gao, Yuguang Fang
Recently, there has been a surge in the development of advanced intelligent generative content (AIGC), especially large language models (LLMs).
no code implementations • 6 Apr 2024 • Danpei Zhao, Bo Yuan, Ziqiang Chen, Tian Li, Zhuoran Liu, Wentao Li, Yue Gao
Experimental results on FineGrip demonstrate the feasibility of the panoptic perception task and the beneficial effect of multi-task joint optimization on individual tasks.
no code implementations • 3 Apr 2024 • Yunsoo Kim, Jinge Wu, Yusuf Abdulle, Yue Gao, Honghan Wu
This work proposes a novel approach to enhance human-computer interaction in chest X-ray analysis using Vision-Language Models (VLMs) enhanced with radiologists' attention by incorporating eye gaze data alongside textual prompts.
no code implementations • 1 Apr 2024 • Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin
Higher-order interactions (HOIs) are ubiquitous in real-world complex systems and applications.
no code implementations • 28 Mar 2024 • Yue Gao, Jiaxuan Lu, Siqi Li, Yipeng Li, Shaoyi Du
By treating segments as vertices and constructing hyperedges using rule-based and KNN-based strategies, a multi-view hypergraph neural network that captures relationships across viewpoint and temporal features is established.
1 code implementation • 25 Mar 2024 • Jiaxuan Lu, Fang Yan, Xiaofan Zhang, Yue Gao, Shaoting Zhang
As natural image understanding moves towards the pretrain-finetune era, research in pathology imaging is concurrently evolving.
1 code implementation • 14 Mar 2024 • Donglin Di, Jiahui Yang, Chaofan Luo, Zhou Xue, Wei Chen, Xun Yang, Yue Gao
Our framework is anchored by a well-established mainflow and an essential module, named ``Geometry and Texture Hypergraph Refiner (HGRefiner)''.
no code implementations • 14 Feb 2024 • Theodore Papamarkou, Tolga Birdal, Michael Bronstein, Gunnar Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Veličković, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
At the same time, this paper serves as an invitation to the scientific community to actively participate in TDL research to unlock the potential of this emerging field.
no code implementations • 6 Feb 2024 • Yifan Feng, Yihe Luo, Shihui Ying, Yue Gao
Experiments on eight hypergraph datasets demonstrate that even without hypergraph dependency, the proposed LightHGNNs can still achieve competitive or even better performance than HGNNs and outperform vanilla MLPs by $16. 3$ on average.
1 code implementation • CVPR 2024 • Yue Gao, Jiahao Li, Lei Chu, Yan Lu
Recent advancements in video modeling extensively rely on optical flow to represent the relationships across frames but this approach often lacks efficiency and fails to model the probability of the intrinsic motion of objects.
no code implementations • CVPR 2024 • Juncheng Mu, Lin Bie, Shaoyi Du, Yue Gao
In this way both geometric and color data can be used thus lead to robust performance even under extremely challenging scenarios such as low overlap between two point clouds.
1 code implementation • CVPR 2024 • Siqi Li, Zhikuan Zhou, Zhou Xue, Yipeng Li, Shaoyi Du, Yue Gao
To achieve this our method leverages a joint framework to predict the 2D feature motion offsets and the 3D feature spatial position simultaneously.
1 code implementation • 16 Dec 2023 • Wentao Li, Danpei Zhao, Bo Yuan, Yue Gao, Zhenwei Shi
Fine-grained object detection (FGOD) extends object detection with the capability of fine-grained recognition.
no code implementations • 14 Dec 2023 • Buqing Nie, Jingtian Ji, Yangqing Fu, Yue Gao
In this work, we propose a novel robust reinforcement learning method called SortRL, which improves the robustness of DRL policies against observation perturbations from the perspective of the network architecture.
no code implementations • 10 Dec 2023 • Bingjun Luo, Haowen Wang, Jinpeng Wang, Junjie Zhu, Xibin Zhao, Yue Gao
With the strong robusticity on illumination variations, near-infrared (NIR) can be an effective and essential complement to visible (VIS) facial expression recognition in low lighting or complete darkness conditions.
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • 10 Dec 2023 • Bingjun Luo, Zewen Wang, Jinpeng Wang, Junjie Zhu, Xibin Zhao, Yue Gao
Illumination variation has been a long-term challenge in real-world facial expression recognition(FER).
Facial Expression Recognition Facial Expression Recognition (FER) +1
no code implementations • 2 Nov 2023 • Zheng Lin, Zhe Chen, Zihan Fang, Xianhao Chen, Xiong Wang, Yue Gao
To this end, we propose FedSN as a general FL framework to tackle the above challenges, and fully explore data diversity on LEO satellites.
1 code implementation • NeurIPS 2023 • Qing Li, Huifang Feng, Kanle Shi, Yue Gao, Yi Fang, Yu-Shen Liu, Zhizhong Han
Specifically, we introduce loss functions to facilitate query points to iteratively reach the moving targets and aggregate onto the approximated surface, thereby learning a global surface representation of the data.
no code implementations • 11 Oct 2023 • Jincheng Wang, Yue Gao
Specifically, we propose a Deep Extreme Mixture Model with Autoencoder (DEMMA) for time series prediction.
no code implementations • 30 Sep 2023 • David Khachaturov, Yue Gao, Ilia Shumailov, Robert Mullins, Ross Anderson, Kassem Fawaz
Visual adversarial examples have so far been restricted to pixel-level image manipulations in the digital world, or have required sophisticated equipment such as 2D or 3D printers to be produced in the physical real world.
no code implementations • 23 Aug 2023 • Yue Gao, Ilia Shumailov, Kassem Fawaz
Machine Learning (ML) systems are vulnerable to adversarial examples, particularly those from query-based black-box attacks.
1 code implementation • 26 Jul 2023 • Yifan Feng, Jiashu Han, Shihui Ying, Yue Gao
The isomorphism problem is a fundamental problem in network analysis, which involves capturing both low-order and high-order structural information.
1 code implementation • 11 Jun 2023 • Yue Gao, Garvesh Raskutti, Rebecca Willet
This paper introduces a novel, computationally-efficient algorithm for predictive inference (PI) that requires no distributional assumptions on the data and can be computed faster than existing bootstrap-type methods for neural networks.
1 code implementation • CVPR 2023 • Qing Li, Huifang Feng, Kanle Shi, Yue Gao, Yi Fang, Yu-Shen Liu, Zhizhong Han
In this work, we introduce signed hyper surfaces (SHS), which are parameterized by multi-layer perceptron (MLP) layers, to learn to estimate oriented normals from point clouds in an end-to-end manner.
no code implementations • 10 May 2023 • Lin Wang, Jiasheng Wu, Yue Gao, Jingjing Zhang
Cloud native technology has revolutionized 5G beyond and 6G communication networks, offering unprecedented levels of operational automation, flexibility, and adaptability.
no code implementations • CVPR 2023 • Yue Gao, Yuan Zhou, Jinglu Wang, Xiao Li, Xiang Ming, Yan Lu
Our method leverages both self-supervised learned landmarks and 3D face model-based landmarks to model the motion.
no code implementations • 26 Mar 2023 • Zheng Lin, Guangyu Zhu, Yiqin Deng, Xianhao Chen, Yue Gao, Kaibin Huang, Yuguang Fang
The increasingly deeper neural networks hinder the democratization of privacy-enhancing distributed learning, such as federated learning (FL), to resource-constrained devices.
no code implementations • CVPR 2023 • Meng Wang, Yu-Shen Liu, Yue Gao, Kanle Shi, Yi Fang, Zhizhong Han
To capture geometry details, current mainstream methods divide 3D shapes into local regions and then learn each one with a local latent code via a decoder, where the decoder shares the geometric similarities among different local regions.
no code implementations • 9 Oct 2022 • Xinwei Zhang, Jianwen Jiang, Yutong Feng, Zhi-Fan Wu, Xibin Zhao, Hai Wan, Mingqian Tang, Rong Jin, Yue Gao
Although a number of studies are devoted to novel category discovery, most of them assume a static setting where both labeled and unlabeled data are given at once for finding new categories.
2 code implementations • 26 Sep 2022 • Mengli Cheng, Yue Gao, Guoqiang Liu, Hongsheng Jin, Xiaowen Zhang
We present EasyRec, an easy-to-use, extendable and efficient recommendation framework for building industrial recommendation systems.
no code implementations • 26 Aug 2022 • Zizhao Zhang, Yifan Feng, Shihui Ying, Yue Gao
To address this issue, we design a general paradigm of deep hypergraph structure learning, namely DeepHGSL, to optimize the hypergraph structure for hypergraph-based representation learning.
no code implementations • 1 Aug 2022 • Xiaolan Liu, Jiadong Yu, Yuanwei Liu, Yue Gao, Toktam Mahmoodi, Sangarapillai Lambotharan, Danny H. K. Tsang
In this paper, we conduct a comprehensive overview of recent advances in distributed intelligence in wireless networks under the umbrella of native-AI wireless networks, with a focus on the basic concepts of native-AI wireless networks, on the AI-enabled edge computing, on the design of distributed learning architectures for heterogeneous networks, on the communication-efficient technologies to support distributed learning, and on the AI-empowered end-to-end communications.
1 code implementation • 19 Jul 2022 • Yue Gao, Abby Stevens, Rebecca Willet, Garvesh Raskutti
Recently, there has been a proliferation of model-agnostic methods to measure variable importance (VI) that analyze the difference in predictive power between a full model trained on all variables and a reduced model that excludes the variable(s) of interest.
1 code implementation • 19 Jul 2022 • Yining Zhao, Chao Wen, Zhou Xue, Yue Gao
We transform the image feature from a cubemap tile to the Hough space of a Manhattan world and directly map the feature to the geometric output.
3D Room Layouts From A Single RGB Panorama Room Layout Estimation
1 code implementation • 19 Jun 2022 • Yue Gao, Ilia Shumailov, Kassem Fawaz, Nicolas Papernot
An example of such a defense is to apply a random transformation to inputs prior to feeding them to the model.
1 code implementation • 2 Jun 2022 • Nan Wang, Shaohui Lin, Xiaoxiao Li, Ke Li, Yunhang Shen, Yue Gao, Lizhuang Ma
U-Nets have achieved tremendous success in medical image segmentation.
1 code implementation • CVPR 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.
1 code implementation • 26 Mar 2022 • Junsheng Zhou, Xin Wen, Baorui Ma, Yu-Shen Liu, Yue Gao, Yi Fang, Zhizhong Han
To address this problem, we present a novel and efficient self-supervised point cloud representation learning framework, named 3D Occlusion Auto-Encoder (3D-OAE), to facilitate the detailed supervision inherited in local regions and global shapes.
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 • 12 Mar 2022 • Fuhai Chen, Xuri Ge, Xiaoshuai Sun, Yue Gao, Jianzhuang Liu, Fufeng Chen, Wenjie Li
The key of referring expression comprehension lies in capturing the cross-modal visual-linguistic relevance.
1 code implementation • 17 Oct 2021 • Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Yongjian Wu, 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 #4 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.
2 code implementations • 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.
1 code implementation • 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.
Ranked #3 on Point Cloud Completion on ShapeNet-ViPC
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.
3 code implementations • 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.
1 code implementation • 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.
Ranked #14 on 3D Semantic Scene Completion on NYUv2
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.
3 code implementations • 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.
1 code implementation • 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.