no code implementations • ICML 2020 • Liu Liu, Lei Deng, Zhaodong Chen, yuke wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie
Using Deep Neural Networks (DNNs) in machine learning tasks is promising in delivering high-quality results but challenging to meet stringent latency requirements and energy constraints because of the memory-bound and the compute-bound execution pattern of DNNs.
3 code implementations • ECCV 2020 • Xiaotong Luo, Yuan Xie, Yulun Zhang, Yanyun Qu, Cuihua Li, Yun Fu
Drawing lessons from lattice filter bank, we design the lattice block (LB) in which two butterfly structures are applied to combine two RBs.
no code implementations • 4 Jun 2024 • Yuzhou Ji, He Zhu, Junshu Tang, Wuyi Liu, Zhizhong Zhang, Yuan Xie, Lizhuang Ma, Xin Tan
The semantically interactive radiance field has always been an appealing task for its potential to facilitate user-friendly and automated real-world 3D scene understanding applications.
no code implementations • 28 May 2024 • Yutao Yang, Jie zhou, Xuanwen Ding, Tianyu Huai, Shunyu Liu, Qin Chen, Liang He, Yuan Xie
Recently, foundation language models (LMs) have marked significant achievements in the domains of natural language processing (NLP) and computer vision (CV).
no code implementations • 22 May 2024 • Jingyang Qiao, Zhizhong Zhang, Xin Tan, Yanyun Qu, Wensheng Zhang, Yuan Xie
Based on the hypothesis that old tasks should have the same results after model updated, we introduce orthogonal gradient projection into different PET paradigms and theoretically demonstrate that the orthogonal condition for the gradient can effectively resist forgetting in PET-based continual methods.
no code implementations • 17 May 2024 • Xin Tan, Wenbin Wu, Zhiwei Zhang, Chaojie Fan, Yong Peng, Zhizhong Zhang, Yuan Xie, Lizhuang Ma
Nevertheless, current models still encounter two main challenges: modeling depth accurately in the 2D-3D view transformation stage, and overcoming the lack of generalizability issues due to sparse LiDAR supervision.
1 code implementation • 12 May 2024 • Haoming Chen, Zhizhong Zhang, Yanyun Qu, Ruixin Zhang, Xin Tan, Yuan Xie
Such inconsiderate consistency greatly hampers the promising path of reaching an universal pre-training framework: (1) The cross-scene semantic self-conflict, i. e., the intense collision between primitive segments of the same semantics from different scenes; (2) Lacking a globally unified bond that pushes the cross-scene semantic consistency into 3D representation learning.
no code implementations • 9 May 2024 • Xiangbo Yin, Jiangming Shi, Yachao Zhang, Yang Lu, Zhizhong Zhang, Yuan Xie, Yanyun Qu
Unsupervised Visible-Infrared Person Re-identification (USVI-ReID) presents a formidable challenge, which aims to match pedestrian images across visible and infrared modalities without any annotations.
no code implementations • 19 Apr 2024 • Jingqun Tang, Chunhui Lin, Zhen Zhao, Shu Wei, Binghong Wu, Qi Liu, Hao Feng, Yang Li, Siqi Wang, Lei Liao, Wei Shi, Yuliang Liu, Hao liu, Yuan Xie, Xiang Bai, Can Huang
Text-centric visual question answering (VQA) has made great strides with the development of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of leading models like GPT4V and Gemini, partly due to a lack of extensive, high-quality instruction tuning data.
2 code implementations • 8 Apr 2024 • Xiaofan Li, Zhizhong Zhang, Xin Tan, Chengwei Chen, Yanyun Qu, Yuan Xie, Lizhuang Ma
The vision-language model has brought great improvement to few-shot industrial anomaly detection, which usually needs to design of hundreds of prompts through prompt engineering.
no code implementations • 4 Mar 2024 • Jingyu Gong, Min Wang, Wentao Liu, Chen Qian, Zhizhong Zhang, Yuan Xie, Lizhuang Ma
To handle this problem, we propose the first Dynamic Environment MOtion Synthesis framework (DEMOS) to predict future motion instantly according to the current scene, and use it to dynamically update the latent motion for final motion synthesis.
no code implementations • 29 Feb 2024 • Jiangming Shi, Xiangbo Yin, Yaoxing Wang, Xiaofeng Liu, Yuan Xie, Yanyun Qu
To address the problem, we propose a Progressive Contrastive Learning with Multi-Prototype (PCLMP) method for USVI-ReID.
no code implementations • 12 Jan 2024 • Jiangming Shi, Xiangbo Yin, Yeyun Chen, Yachao Zhang, Zhizhong Zhang, Yuan Xie, Yanyun Qu
To associate cross-modality clustered pseudo-labels, we design a Multi-Memory Learning and Matching (MMLM) module, ensuring that optimization explicitly focuses on the nuances of individual perspectives and establishes reliable cross-modality correspondences.
1 code implementation • 14 Dec 2023 • Jiangming Shi, Shanshan Zheng, Xiangbo Yin, Yang Lu, Yuan Xie, Yanyun Qu
For server-side learning, in order to mitigate the heterogeneity and class-distribution imbalance, we generate federated features to retrain the server model.
no code implementations • 13 Dec 2023 • Yujun Chen, Xin Tan, Zhizhong Zhang, Yanyun Qu, Yuan Xie
Second, in the Image Branch, we propose the Instance Position-scale Learning (IPSL) Module to learn and fuse the information of instance position and scale, which is from a 2D pre-trained detector and a type of latent label obtained from 3D to 2D projection.
1 code implementation • 4 Dec 2023 • Qihang Ma, Xin Tan, Yanyun Qu, Lizhuang Ma, Zhizhong Zhang, Yuan Xie
The autonomous driving community has shown significant interest in 3D occupancy prediction, driven by its exceptional geometric perception and general object recognition capabilities.
1 code implementation • 22 Nov 2023 • Zhen Zhao, Jingqun Tang, Chunhui Lin, Binghong Wu, Can Huang, Hao liu, Xin Tan, Zhizhong Zhang, Yuan Xie
A straightforward solution is performing model fine-tuning tailored to a specific scenario, but it is computationally intensive and requires multiple model copies for various scenarios.
1 code implementation • 20 Nov 2023 • Zhengyuan Peng, Qijian Tian, Jianqing Xu, Yizhang Jin, Xuequan Lu, Xin Tan, Yuan Xie, Lizhuang Ma
This paper explores a novel setting called Generalized Category Discovery in Semantic Segmentation (GCDSS), aiming to segment unlabeled images given prior knowledge from a labeled set of base classes.
1 code implementation • ICCV 2023 • Zhiwei Zhang, Zhizhong Zhang, Qian Yu, Ran Yi, Yuan Xie, Lizhuang Ma
3D panoptic segmentation is a challenging perception task that requires both semantic segmentation and instance segmentation.
no code implementations • 12 Jun 2023 • Ji Xu, Yuan Xie, Wenchao Wang
Underwater acoustic target recognition is a challenging task owing to the intricate underwater environments and limited data availability.
no code implementations • 31 May 2023 • Tianyu Chen, Yuan Xie, Shuai Zhang, Shaohan Huang, Haoyi Zhou, JianXin Li
Music representation learning is notoriously difficult for its complex human-related concepts contained in the sequence of numerical signals.
no code implementations • 31 May 2023 • Yuan Xie, Jiawei Ren, Ji Xu
In our work, we propose to implement Underwater Acoustic Recognition based on Templates made up of rich relevant information (hereinafter called "UART").
no code implementations • 31 May 2023 • Yuan Xie, Jiawei Ren, Ji Xu
Background noise and variable channel transmission environment make it complicated to implement accurate ship-radiated noise recognition.
no code implementations • 24 Apr 2023 • Yuan Xie, Tianyu Chen, Ji Xu
Underwater acoustic recognition for ship-radiated signals has high practical application value due to the ability to recognize non-line-of-sight targets.
no code implementations • 18 Apr 2023 • Yuanwei Fang, Zihao Liu, Yanheng Lu, Jiawei Liu, Jiajie Li, Yi Jin, Jian Chen, Yenkuang Chen, Hongzhong Zheng, Yuan Xie
Furthermore, NPS shows higher accuracy and generality than the state-of-the-art GNN approach in code behavior learning, enabling the generation of high-quality execution embeddings.
1 code implementation • 15 Mar 2023 • Jinxiang Lai, Siqian Yang, Wenlong Wu, Tao Wu, Guannan Jiang, Xi Wang, Jun Liu, Bin-Bin Gao, Wei zhang, Yuan Xie, Chengjie Wang
Then we derive two specific attention modules, named SpatialFormer Semantic Attention (SFSA) and SpatialFormer Target Attention (SFTA), to enhance the target object regions while reduce the background distraction.
1 code implementation • 7 Feb 2023 • Yanbo Wang, Chuming Lin, Donghao Luo, Ying Tai, Zhizhong Zhang, Yuan Xie
A generic method for generating a high-quality image from the degraded one is in demand.
no code implementations • CVPR 2023 • Jin Lin, Xiaotong Luo, Ming Hong, Yanyun Qu, Yuan Xie, Zongze Wu
In the forward stage, we take advantage of LTH with rewinding weights to progressively shrink the SR model and the pruning-out masks that form nested sets.
1 code implementation • CVPR 2023 • Tenghao Cai, Zhizhong Zhang, Xin Tan, Yanyun Qu, Guannan Jiang, Chengjie Wang, Yuan Xie
As a result, our dynamic inference network is trained independently of baseline and provides a flexible, efficient solution to distinguish between tasks.
no code implementations • CVPR 2023 • Zhen Zhao, Zhizhong Zhang, Xin Tan, Jun Liu, Yanyun Qu, Yuan Xie, Lizhuang Ma
In this paper, we propose a space decoupling (SD) algorithm to decouple the feature space into a pair of complementary subspaces, i. e., the stability space I, and the plasticity space R. I is established by conducting space intersection between the historic and current feature space, and thus I contains more task-shared bases.
1 code implementation • ICCV 2023 • Jiangming Shi, Yachao Zhang, Xiangbo Yin, Yuan Xie, Zhizhong Zhang, Jianping Fan, Zhongchao shi, Yanyun Qu
Visible-infrared person re-identification (VI-ReID) aims to match a specific person from a gallery of images captured from non-overlapping visible and infrared cameras.
no code implementations • ICCV 2023 • Xudong Tian, Zhizhong Zhang, Xin Tan, Jun Liu, Chengjie Wang, Yanyun Qu, Guannan Jiang, Yuan Xie
Continual Learning (CL) is the constant development of complex behaviors by building upon previously acquired skills.
6 code implementations • AAAI 2021 • Yachao Zhang, Zonghao Li, Yuan Xie, Yanyun Qu, Cuihua Li, Tao Mei
Firstly, we construct a pretext task, \textit{i. e.,} point cloud colorization, with a self-supervised learning to transfer the learned prior knowledge from a large amount of unlabeled point cloud to a weakly supervised network.
no code implementations • 23 Nov 2022 • Jiawei Zhan, Jun Liu, Wei Tang, Guannan Jiang, Xi Wang, Bin-Bin Gao, Tianliang Zhang, Wenlong Wu, Wei zhang, Chengjie Wang, Yuan Xie
This paper builds a unified framework to perform effective noisy-proposal suppression and to interact between global and local features for robust feature learning.
1 code implementation • 16 Nov 2022 • Xinyao Shu, ShiYang Yan, Zhenyu Lu, Xinshao Wang, Yuan Xie
Unsupervised domain adaption (UDA) is a transfer learning task where the data and annotations of the source domain are available but only have access to the unlabeled target data during training.
1 code implementation • 12 Nov 2022 • Xuehui Dong, Rujing Xiong, Tiebin Mi, Yuan Xie, Robert Caiming Qiu
This paper investigates the problem of maximizing the signal-to-noise ratio (SNR) in reconfigurable intelligent surface (RIS)-assisted MISO communication systems.
no code implementations • 10 Nov 2022 • Haiyang Lin, Mingyu Yan, Xiaochun Ye, Dongrui Fan, Shirui Pan, WenGuang Chen, Yuan Xie
This situation poses a considerable challenge for newcomers, hindering their ability to grasp a comprehensive understanding of the workflows, computational patterns, communication strategies, and optimization techniques employed in distributed GNN training.
no code implementations • 2 Nov 2022 • Jinxiang Lai, Siqian Yang, Guannan Jiang, Xi Wang, Yuxi Li, Zihui Jia, Xiaochen Chen, Jun Liu, Bin-Bin Gao, Wei zhang, Yuan Xie, Chengjie Wang
In this paper, for the first time, we investigate the contributions of different distance metrics, and propose an adaptive fusion scheme, bringing significant improvements in few-shot classification.
1 code implementation • 23 Sep 2022 • Boyuan Feng, Tianqi Tang, yuke wang, Zhaodong Chen, Zheng Wang, Shu Yang, Yuan Xie, Yufei Ding
In this paper, we propose Faith, an efficient framework for transformer verification on GPUs.
no code implementations • 16 Sep 2022 • Tianfang Sun, Zhizhong Zhang, Xin Tan, Yanyun Qu, Yuan Xie, Lizhuang Ma
In this paper, we propose a novel cross-modality weakly supervised method for 3D segmentation, incorporating complementary information from unlabeled images.
no code implementations • 5 Sep 2022 • Junshu Tang, Jiachen Xu, Jingyu Gong, Haichuan Song, Yuan Xie, Lizhuang Ma
Moreover, for effective training, we consider difficulty-based sampling strategy to encourage the network to pay more attention to some partial point clouds with fewer geometric information.
no code implementations • 31 Aug 2022 • Ding Li, Yuan Xie, Wensheng Zhang, Yongqiang Tang, Zhizhong Zhang
However, the existing methods simply employed max/average pooling in this framework, which ignored the distinct contributions of different individuals to the group activity recognition.
1 code implementation • 30 Aug 2022 • Zhifeng Xie, Sen Wang, Ke Xu, Zhizhong Zhang, Xin Tan, Yuan Xie, Lizhuang Ma
Based on this, we propose to exploit the image frequency distributions for night-time scene parsing.
1 code implementation • 11 Aug 2022 • Zejiang Hou, Fei Sun, Yen-Kuang Chen, Yuan Xie, Sun-Yuan Kung
When the masked autoencoder is pretrained and finetuned on ImageNet-1K dataset with an input resolution of 224x224, MILAN achieves a top-1 accuracy of 85. 4% on ViT-Base, surpassing previous state-of-the-arts by 1%.
1 code implementation • 28 Jul 2022 • Zhaoyang Du, Yijin Guan, Tianchan Guan, Dimin Niu, Nianxiong Tan, Xiaopeng Yu, Hongzhong Zheng, Jianyi Meng, Xiaolang Yan, Yuan Xie
We also propose a reference design of the existing sampling-based method with optimized computing overheads to demonstrate the better accuracy of the proposed method.
no code implementations • 19 Jul 2022 • Yuan Xie, Shaohan Huang, Tianyu Chen, Furu Wei
Sparsely Mixture of Experts (MoE) has received great interest due to its promising scaling capability with affordable computational overhead.
3 code implementations • 20 Jun 2022 • Xudong Tian, Zhizhong Zhang, Cong Wang, Wensheng Zhang, Yanyun Qu, Lizhuang Ma, Zongze Wu, Yuan Xie, DaCheng Tao
Information Bottleneck (IB) based multi-view learning provides an information theoretic principle for seeking shared information contained in heterogeneous data descriptions.
1 code implementation • 4 Jun 2022 • Zihao Zhao, Yanhong Wang, Qiaosha Zou, Tie XU, Fangbo Tao, Jiansong Zhang, Xiaoan Wang, C. -J. Richard Shi, Junwen Luo, Yuan Xie
At last, we conclude the few-shot learning paradigm of the developed network: 1) a hierarchical structure-based network design involves human prior knowledge; 2) SNNs for content based global dynamic feature detection.
no code implementations • 1 Jun 2022 • Tianyu Chen, Shaohan Huang, Yuan Xie, Binxing Jiao, Daxin Jiang, Haoyi Zhou, JianXin Li, Furu Wei
The sparse Mixture-of-Experts (MoE) model is powerful for large-scale pre-training and has achieved promising results due to its model capacity.
2 code implementations • 11 May 2022 • Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang
The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.
no code implementations • 12 Apr 2022 • Ling Liang, Kaidi Xu, Xing Hu, Lei Deng, Yuan Xie
To the best of our knowledge, this is the first analysis on robust training of SNNs.
1 code implementation • CVPR 2022 • Junshu Tang, Zhijun Gong, Ran Yi, Yuan Xie, Lizhuang Ma
An asymmetric keypoint locator, including an unsupervised multi-scale keypoint detector and a complete keypoint generator, is proposed for localizing aligned keypoints from complete and partial point clouds.
1 code implementation • CVPR 2022 • Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung
However, conventional pruning methods have limitations in that: they are restricted to pruning process only, and they require a fully pre-trained large model.
no code implementations • 28 Feb 2022 • Zhaodong Chen, Yuying Quan, Zheng Qu, Liu Liu, Yufei Ding, Yuan Xie
We evaluate the 1:2 and 2:4 sparsity under different configurations and achieve 1. 27~ 1. 89x speedups over the full-attention mechanism.
no code implementations • 10 Feb 2022 • Xin Liu, Mingyu Yan, Lei Deng, Guoqi Li, Xiaochun Ye, Dongrui Fan, Shirui Pan, Yuan Xie
Next, we provide comparisons from aspects of the efficiency and characteristics of these methods.
1 code implementation • 20 Jan 2022 • Nan Wu, Jiwon Lee, Yuan Xie, Cong Hao
Despite the stride made by machine learning (ML) based performance modeling, two major concerns that may impede production-ready ML applications in EDA are stringent accuracy requirements and generalization capability.
no code implementations • 18 Jan 2022 • Nan Wu, Hang Yang, Yuan Xie, Pan Li, Cong Hao
The contribution of this work is three-fold.
no code implementations • CVPR 2022 • Xia Kong, Zuodong Gao, Xiaofan Li, Ming Hong, Jun Liu, Chengjie Wang, Yuan Xie, Yanyun Qu
Our ICCE promotes intra-class compactness with inter-class separability on both seen and unseen classes in the embedding space and visual feature space.
1 code implementation • CVPR 2022 • Mengtian Li, Yuan Xie, Yunhang Shen, Bo Ke, Ruizhi Qiao, Bo Ren, Shaohui Lin, Lizhuang Ma
To address the huge labeling cost in large-scale point cloud semantic segmentation, we propose a novel hybrid contrastive regularization (HybridCR) framework in weakly-supervised setting, which obtains competitive performance compared to its fully-supervised counterpart.
no code implementations • 21 Dec 2021 • Minghai Qin, Tianyun Zhang, Fei Sun, Yen-Kuang Chen, Makan Fardad, Yanzhi Wang, Yuan Xie
Deep neural networks (DNNs) have shown to provide superb performance in many real life applications, but their large computation cost and storage requirement have prevented them from being deployed to many edge and internet-of-things (IoT) devices.
1 code implementation • 21 Dec 2021 • Tianshui Chen, Tao Pu, Hefeng Wu, Yuan Xie, Liang Lin
To reduce the annotation cost, we propose a structured semantic transfer (SST) framework that enables training multi-label recognition models with partial labels, i. e., merely some labels are known while other labels are missing (also called unknown labels) per image.
no code implementations • 20 Dec 2021 • Fei Sun, Minghai Qin, Tianyun Zhang, Xiaolong Ma, Haoran Li, Junwen Luo, Zihao Zhao, Yen-Kuang Chen, Yuan Xie
Our experiments show that GS patterns consistently make better trade-offs between accuracy and computation efficiency compared to conventional structured sparse patterns.
no code implementations • 26 Nov 2021 • Anbang Wu, Gushu Li, yuke wang, Boyuan Feng, Yufei Ding, Yuan Xie
In this paper, we propose a novel training scheme to mitigate such noise-induced gradient vanishing.
1 code implementation • 25 Nov 2021 • Jiachen Xu, Min Wang, Jingyu Gong, Wentao Liu, Chen Qian, Yuan Xie, Lizhuang Ma
Prior plays an important role in providing the plausible constraint on human motion.
no code implementations • 25 Nov 2021 • Anbang Wu, Gushu Li, Yufei Ding, Yuan Xie
In this paper, we propose a novel training scheme to mitigate such noise-induced gradient vanishing.
no code implementations • 21 Oct 2021 • Liu Liu, Zheng Qu, Zhaodong Chen, Yufei Ding, Yuan Xie
We demonstrate that the sparse patterns are dynamic, depending on input sequences.
no code implementations • 18 Oct 2021 • Hengrui Zhang, Zhongming Yu, Guohao Dai, Guyue Huang, Yufei Ding, Yuan Xie, Yu Wang
The same data are propagated through the graph structure to perform the same neural operation multiple times in GNNs, leading to redundant computation which accounts for 92. 4% of total operators.
no code implementations • 29 Sep 2021 • Zhaodong Chen, Liu Liu, Yuying Quan, Zheng Qu, Yufei Ding, Yuan Xie
Transformers are becoming mainstream solutions for various tasks like NLP and Computer vision.
no code implementations • 29 Sep 2021 • Haiyan Wu, Yuting Gao, Ke Li, Yinqi Zhang, Shaohui Lin, Yuan Xie, Xing Sun
These findings motivate us to introduce an self-supervised teaching assistant (SSTA) besides the commonly used supervised teacher to improve the performance of transformers.
no code implementations • 13 Sep 2021 • Nan Wu, Huake He, Yuan Xie, Pan Li, Cong Hao
Pioneering in this direction, we expect more GNN endeavors to revolutionize this high-demand Program-to-Circuit problem and to enrich the expressiveness of GNNs on programs.
no code implementations • 25 Jul 2021 • Ling Liang, Zheng Qu, Zhaodong Chen, Fengbin Tu, Yujie Wu, Lei Deng, Guoqi Li, Peng Li, Yuan Xie
Although spiking neural networks (SNNs) take benefits from the bio-plausible neural modeling, the low accuracy under the common local synaptic plasticity learning rules limits their application in many practical tasks.
no code implementations • 30 Jun 2021 • Shubao Liu, Ke-Yue Zhang, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Yuan Xie, Lizhuang Ma
Face anti-spoofing approaches based on domain generalization (DG) have drawn growing attention due to their robustness for unseen scenarios.
no code implementations • 18 Jun 2021 • Chengwei Chen, Yuan Xie, Shaohui Lin, Ruizhi Qiao, Jian Zhou, Xin Tan, Yi Zhang, Lizhuang Ma
Moreover, our model is more stable for training in a non-adversarial manner, compared to other adversarial based novelty detection methods.
1 code implementation • ICLR 2022 • Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie
It addresses the shortcomings of the previous works by repeatedly growing a subset of layers to dense and then pruning them back to sparse after some training.
8 code implementations • 25 May 2021 • Yanbo Wang, Shaohui Lin, Yanyun Qu, Haiyan Wu, Zhizhong Zhang, Yuan Xie, Angela Yao
Convolutional neural networks (CNNs) are highly successful for super-resolution (SR) but often require sophisticated architectures with heavy memory cost and computational overhead, significantly restricts their practical deployments on resource-limited devices.
4 code implementations • CVPR 2021 • Jingyu Gong, Jiachen Xu, Xin Tan, Haichuan Song, Yanyun Qu, Yuan Xie, Lizhuang Ma
Our method can significantly improve the backbones in all three datasets.
Ranked #2 on Semantic Segmentation on Semantic3D
no code implementations • CVPR 2021 • ShiYang Yan, Li Yu, Yuan Xie
We propose a novel attention scheme which projects the image and text embedding into a common space and optimises the attention weights directly towards the evaluation metrics.
7 code implementations • CVPR 2021 • Haiyan Wu, Yanyun Qu, Shaohui Lin, Jian Zhou, Ruizhi Qiao, Zhizhong Zhang, Yuan Xie, Lizhuang Ma
In this paper, we propose a novel contrastive regularization (CR) built upon contrastive learning to exploit both the information of hazy images and clear images as negative and positive samples, respectively.
Ranked #5 on Image Dehazing on RS-Haze
3 code implementations • CVPR 2021 • Xudong Tian, Zhizhong Zhang, Shaohui Lin, Yanyun Qu, Yuan Xie, Lizhuang Ma
The Information Bottleneck (IB) provides an information theoretic principle for representation learning, by retaining all information relevant for predicting label while minimizing the redundancy.
Cross-Modality Person Re-identification Cross-Modal Person Re-Identification +3
no code implementations • 11 Mar 2021 • Xinfeng Xie, Peng Gu, Yufei Ding, Dimin Niu, Hongzhong Zheng, Yuan Xie
For general purpose scenarios, lightweight hardware designs for diverse data paths, architectural supports for the SIMT programming model, and end-to-end software optimizations remain challenging.
Hardware Architecture
no code implementations • 11 Mar 2021 • Chenhaoping Wen, Jingjing Gao, Yuan Xie, Qing Zhang, Pengfei Kong, Jinghui Wang, Yilan Jiang, Xuan Luo, Jun Li, Wenjian Lu, Yu-Ping Sun, Shichao Yan
4$H_{\rm b}$-TaS$_2$ is a superconducting compound with alternating 1$T$-TaS$_2$ and 1$H$-TaS$_2$ layers, where the 1$H$-TaS$_2$ layer has weak charge density wave (CDW) pattern and reduces the CDW coupling between the adjacent 1$T$-TaS$_2$ layers.
Mesoscale and Nanoscale Physics Materials Science
no code implementations • 2 Mar 2021 • Eren Kurshan, Hai Li, Mingoo Seok, Yuan Xie
Over the last decade, artificial intelligence has found many applications areas in the society.
no code implementations • 16 Feb 2021 • Nan Wu, Yuan Xie
Then, we summarize the common problems in computer architecture/system design that can be solved by ML techniques, and the typical ML techniques employed to resolve each of them.
no code implementations • 16 Feb 2021 • Nan Wu, Yuan Xie, Cong Hao
Despite the great success of High-Level Synthesis (HLS) tools, we observe several unresolved challenges: 1) the high-level abstraction of programming styles in HLS sometimes conceals optimization opportunities; 2) existing HLS tools do not provide flexible trade-off (Pareto) solutions among different objectives and constraints; 3) the actual quality of the resulting RTL designs is hard to predict.
no code implementations • Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence 2021 • Xuncheng Liu, Xudong Tian, Shaohui Lin, Yanyun Qu, Lizhuang Ma, Wang Yuan, Zhizhong Zhang, Yuan Xie
In this paper, we present a novel purified memory mechanism that simulates the recognition process of human beings.
no code implementations • 7 Jan 2021 • Jingyu Gong, Jiachen Xu, Xin Tan, Jie zhou, Yanyun Qu, Yuan Xie, Lizhuang Ma
Boundary information plays a significant role in 2D image segmentation, while usually being ignored in 3D point cloud segmentation where ambiguous features might be generated in feature extraction, leading to misclassification in the transition area between two objects.
no code implementations • 1 Jan 2021 • Zhaodong Chen, Zhao WeiQin, Lei Deng, Guoqi Li, Yuan Xie
Moreover, analysis on the activation's mean in the forward pass reveals that the self-normalization property gets weaker with larger fan-in of each layer, which explains the performance degradation on large benchmarks like ImageNet.
7 code implementations • ICCV 2021 • Yachao Zhang, Yanyun Qu, Yuan Xie, Zonghao Li, Shanshan Zheng, Cuihua Li
In this way, the graph topology of the whole point cloud can be effectively established by the introduced auxiliary supervision, such that the information propagation between the labeled and unlabeled points will be realized.
1 code implementation • 29 Dec 2020 • Tao Pu, Tianshui Chen, Yuan Xie, Hefeng Wu, Liang Lin
In this work, we explore the correlations among the action units and facial expressions, and devise an AU-Expression Knowledge Constrained Representation Learning (AUE-CRL) framework to learn the AU representations without AU annotations and adaptively use representations to facilitate facial expression recognition.
Facial Expression Recognition Facial Expression Recognition (FER) +1
no code implementations • 30 Nov 2020 • Jiayi Yang, Lei Deng, Yukuan Yang, Yuan Xie, Guoqi Li
However, neural network quantization can be used to reduce computation load while maintaining comparable accuracy and original network structure.
no code implementations • 26 Sep 2020 • Xiaobing Chen, yuke wang, Xinfeng Xie, Xing Hu, Abanti Basak, Ling Liang, Mingyu Yan, Lei Deng, Yufei Ding, Zidong Du, Yunji Chen, Yuan Xie
Graph convolutional network (GCN) emerges as a promising direction to learn the inductive representation in graph data commonly used in widespread applications, such as E-commerce, social networks, and knowledge graphs.
Hardware Architecture
1 code implementation • 3 Aug 2020 • Yuan Xie, Tianshui Chen, Tao Pu, Hefeng Wu, Liang Lin
However, most of these works focus on holistic feature adaptation, and they ignore local features that are more transferable across different datasets.
Cross-Domain Facial Expression Recognition Facial Expression Recognition (FER)
1 code implementation • 3 Aug 2020 • Tianshui Chen, Tao Pu, Hefeng Wu, Yuan Xie, Lingbo Liu, Liang Lin
Although each declares to achieve superior performance, fair comparisons are lacking due to the inconsistent choices of the source/target datasets and feature extractors.
Ranked #1 on Cross-Domain Facial Expression Recognition on Source: AFE, Target: CK+, JAFFE, SFEW2.0, FER2013, ExpW
Cross-Domain Facial Expression Recognition Domain Adaptation +3
no code implementations • 9 Jul 2020 • Nan Wang, Chengwei Chen, Yuan Xie, Lizhuang Ma
The brain structure in the collected data is complicated, thence, doctors are required to spend plentiful energy when diagnosing brain abnormalities.
Semi-supervised Anomaly Detection Supervised Anomaly Detection
1 code implementation • 11 Jun 2020 • Yuke Wang, Boyuan Feng, Gushu Li, Shuangchen Li, Lei Deng, Yuan Xie, Yufei Ding
As the emerging trend of graph-based deep learning, Graph Neural Networks (GNNs) excel for their capability to generate high-quality node feature vectors (embeddings).
Distributed, Parallel, and Cluster Computing
no code implementations • 7 May 2020 • Codruta O. Ancuti, Cosmin Ancuti, Florin-Alexandru Vasluianu, Radu Timofte, Jing Liu, Haiyan Wu, Yuan Xie, Yanyun Qu, Lizhuang Ma, Ziling Huang, Qili Deng, Ju-Chin Chao, Tsung-Shan Yang, Peng-Wen Chen, Po-Min Hsu, Tzu-Yi Liao, Chung-En Sun, Pei-Yuan Wu, Jeonghyeok Do, Jongmin Park, Munchurl Kim, Kareem Metwaly, Xuelu Li, Tiantong Guo, Vishal Monga, Mingzhao Yu, Venkateswararao Cherukuri, Shiue-Yuan Chuang, Tsung-Nan Lin, David Lee, Jerome Chang, Zhan-Han Wang, Yu-Bang Chang, Chang-Hong Lin, Yu Dong, Hong-Yu Zhou, Xiangzhen Kong, Sourya Dipta Das, Saikat Dutta, Xuan Zhao, Bing Ouyang, Dennis Estrada, Meiqi Wang, Tianqi Su, Siyi Chen, Bangyong Sun, Vincent Whannou de Dravo, Zhe Yu, Pratik Narang, Aryan Mehra, Navaneeth Raghunath, Murari Mandal
We focus on the proposed solutions and their results evaluated on NH-Haze, a novel dataset consisting of 55 pairs of real haze free and nonhomogeneous hazy images recorded outdoor.
no code implementations • 7 May 2020 • Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin
We present SmartExchange, an algorithm-hardware co-design framework to trade higher-cost memory storage/access for lower-cost computation, for energy-efficient inference of deep neural networks (DNNs).
no code implementations • 6 May 2020 • Shanxin Yuan, Radu Timofte, Ales Leonardis, Gregory Slabaugh, Xiaotong Luo, Jiangtao Zhang, Yanyun Qu, Ming Hong, Yuan Xie, Cuihua Li, Dejia Xu, Yihao Chu, Qingyan Sun, Shuai Liu, Ziyao Zong, Nan Nan, Chenghua Li, Sangmin Kim, Hyungjoon Nam, Jisu Kim, Jechang Jeong, Manri Cheon, Sung-Jun Yoon, Byungyeon Kang, Junwoo Lee, Bolun Zheng, Xiaohong Liu, Linhui Dai, Jun Chen, Xi Cheng, Zhen-Yong Fu, Jian Yang, Chul Lee, An Gia Vien, Hyunkook Park, Sabari Nathan, M. Parisa Beham, S Mohamed Mansoor Roomi, Florian Lemarchand, Maxime Pelcat, Erwan Nogues, Densen Puthussery, Hrishikesh P. S, Jiji C. V, Ashish Sinha, Xuan Zhao
Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image.
no code implementations • 3 May 2020 • Weitao Li, Pengfei Xu, Yang Zhao, Haitong Li, Yuan Xie, Yingyan Lin
Resistive-random-access-memory (ReRAM) based processing-in-memory (R$^2$PIM) accelerators show promise in bridging the gap between Internet of Thing devices' constrained resources and Convolutional/Deep Neural Networks' (CNNs/DNNs') prohibitive energy cost.
1 code implementation • 2 May 2020 • Weihua He, Yujie Wu, Lei Deng, Guoqi Li, Haoyu Wang, Yang Tian, Wei Ding, Wenhui Wang, Yuan Xie
Neuromorphic data, recording frameless spike events, have attracted considerable attention for the spatiotemporal information components and the event-driven processing fashion.
Ranked #13 on Gesture Recognition on DVS128 Gesture
no code implementations • 24 Apr 2020 • Fei Sun, Minghai Qin, Tianyun Zhang, Liu Liu, Yen-Kuang Chen, Yuan Xie
We show that for practically complicated problems, it is more beneficial to search large and sparse models in the weight dominated region.
no code implementations • 19 Feb 2020 • Tong Wu, Yuan Xie, Yanyun Qu, Bicheng Dai, Shuxin Chen
MSN can fast generate the weights of fusion layers through a simple meta-learner, requiring only a few training samples and epochs to converge.
no code implementations • 5 Feb 2020 • Chengwei Chen, Pan Chen, Haichuan Song, Yiqing Tao, Yuan Xie, Shouhong Ding, Lizhuang Ma
Anomaly detection is a fundamental problem in computer vision area with many real-world applications.
no code implementations • 4 Feb 2020 • Chengwei Chen, Pan Chen, Lingyu Yang, Jinyuan Mo, Haichuan Song, Yuan Xie, Lizhuang Ma
Acoustic anomaly detection aims at distinguishing abnormal acoustic signals from the normal ones.
no code implementations • 3 Feb 2020 • Chengwei Chen, Wang Yuan, Yuan Xie, Yanyun Qu, Yiqing Tao, Haichuan Song, Lizhuang Ma
One-class novelty detection is the process of determining if a query example differs from the training examples (the target class).
1 code implementation • 24 Jan 2020 • Jiachen Xu, Jingyu Gong, Jie zhou, Xin Tan, Yuan Xie, Lizhuang Ma
Besides local features, global information plays an essential role in semantic segmentation, while recent works usually fail to explicitly extract the meaningful global information and make full use of it.
no code implementations • 20 Jan 2020 • Nan Wu, Adrien Vincent, Dmitri Strukov, Yuan Xie
Namely, neuromorphic architectures that leverage memristors, the programmable and nonvolatile two-terminal devices, as synaptic weights in hardware neural networks, are candidates of choice to realize such highly energy-efficient and complex nervous systems.
1 code implementation • 7 Jan 2020 • Mingyu Yan, Lei Deng, Xing Hu, Ling Liang, Yujing Feng, Xiaochun Ye, Zhimin Zhang, Dongrui Fan, Yuan Xie
In this work, we first characterize the hybrid execution patterns of GCNs on Intel Xeon CPU.
Distributed, Parallel, and Cluster Computing
1 code implementation • 1 Jan 2020 • Zhaodong Chen, Lei Deng, Bangyan Wang, Guoqi Li, Yuan Xie
Powered by our metric and framework, we analyze extensive initialization, normalization, and network structures.
no code implementations • 1 Jan 2020 • Ling Liang, Xing Hu, Lei Deng, Yujie Wu, Guoqi Li, Yufei Ding, Peng Li, Yuan Xie
Recently, backpropagation through time inspired learning algorithms are widely introduced into SNNs to improve the performance, which brings the possibility to attack the models accurately given Spatio-temporal gradient maps.
no code implementations • 28 Nov 2019 • Gushu Li, Li Zhou, Nengkun Yu, Yufei Ding, Mingsheng Ying, Yuan Xie
In this paper, we propose Proq, a runtime assertion scheme for testing and debugging quantum programs on a quantum computer.
no code implementations • 19 Nov 2019 • Ao Ren, Tao Zhang, Yuhao Wang, Sheng Lin, Peiyan Dong, Yen-Kuang Chen, Yuan Xie, Yanzhi Wang
As a further optimization, we propose a density-adaptive regular-block (DARB) pruning that outperforms prior structured pruning work with high pruning ratio and decoding efficiency.
1 code implementation • 3 Nov 2019 • Lei Deng, Yujie Wu, Yifan Hu, Ling Liang, Guoqi Li, Xing Hu, Yufei Ding, Peng Li, Yuan Xie
As well known, the huge memory and compute costs of both artificial neural networks (ANNs) and spiking neural networks (SNNs) greatly hinder their deployment on edge devices with high efficiency.
no code implementations • 25 Sep 2019 • Liu Liu, Lei Deng, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie
Using Recurrent Neural Networks (RNNs) in sequence modeling tasks is promising in delivering high-quality results but challenging to meet stringent latency requirements because of the memory-bound execution pattern of RNNs.
no code implementations • 25 Sep 2019 • Peiqi Wang, Yu Ji, Xinfeng Xie, Yongqiang Lyu, Dongsheng Wang, Yuan Xie
Despite the success in model reduction of convolutional neural networks (CNNs), neural network quantization methods have not yet been studied on GANs, which are mainly faced with the issues of both the effectiveness of quantization algorithms and the instability of training GAN models.
2 code implementations • 5 Sep 2019 • Yukuan Yang, Shuang Wu, Lei Deng, Tianyi Yan, Yuan Xie, Guoqi Li
In this way, all the operations in the training and inference can be bit-wise operations, pushing towards faster processing speed, decreased memory cost, and higher energy efficiency.
no code implementations • 26 Aug 2019 • Yuke Wang, Boyuan Feng, Gushu Li, Lei Deng, Yuan Xie, Yufei Ding
As a promising solution to boost the performance of distance-related algorithms (e. g., K-means and KNN), FPGA-based acceleration attracts lots of attention, but also comes with numerous challenges.
Distributed, Parallel, and Cluster Computing Programming Languages
1 code implementation • ICCV 2019 • Pengxiang Yan, Guanbin Li, Yuan Xie, Zhen Li, Chuan Wang, Tianshui Chen, Liang Lin
Specifically, we present an effective video saliency detector that consists of a spatial refinement network and a spatiotemporal module.
Ranked #1 on Video Salient Object Detection on VOS-T (using extra training data)
no code implementations • ICLR 2019 • Zhaodong Chen, Lei Deng, Guoqi Li, Jiawei Sun, Xing Hu, Ling Liang, YufeiDing, Yuan Xie
We identify that the effectiveness expects less data correlation while the efficiency expects regular execution pattern.
no code implementations • International Conference on Architectural Support for Programming Languages and Operating Systems 2019 • Gushu Li, Yufei Ding, Yuan Xie
Due to little consideration in the hardware constraints, e. g., limited connections between physical qubits to enable two-qubit gates, most quantum algorithms cannot be directly executed on the Noisy Intermediate-Scale Quantum (NISQ) devices.
no code implementations • 10 Mar 2019 • Xing Hu, Ling Liang, Lei Deng, Shuangchen Li, Xinfeng Xie, Yu Ji, Yufei Ding, Chang Liu, Timothy Sherwood, Yuan Xie
As neural networks continue their reach into nearly every aspect of software operations, the details of those networks become an increasingly sensitive subject.
Cryptography and Security Hardware Architecture
no code implementations • 28 Jan 2019 • Yu Ji, Youyang Zhang, Xinfeng Xie, Shuangchen Li, Peiqi Wang, Xing Hu, Youhui Zhang, Yuan Xie
In this paper, we propose a full system stack solution, composed of a reconfigurable architecture design, Field Programmable Synapse Array (FPSA) and its software system including neural synthesizer, temporal-to-spatial mapper, and placement & routing.
no code implementations • 24 Jan 2019 • Peiqi Wang, Dongsheng Wang, Yu Ji, Xinfeng Xie, Haoxuan Song, XuXin Liu, Yongqiang Lyu, Yuan Xie
The intensive computation and memory requirements of generative adversarial neural networks (GANs) hinder its real-world deployment on edge devices such as smartphones.
no code implementations • 3 Jan 2019 • Pengfei Zuo, Yu Hua, Yuan Xie
Specifically, SecPM leverages the CWT scheme to guarantee the crash consistency via ensuring both the data and its counter are durable before the data flush completes, and leverages the CWR scheme to improve the system performance via exploiting the spatial locality of counter storage, log and data writes.
Distributed, Parallel, and Cluster Computing Hardware Architecture Cryptography and Security
no code implementations • 10 Dec 2018 • Lingbo Liu, Guanbin Li, Yuan Xie, Yizhou Yu, Qing Wang, Liang Lin
In this paper, we propose a novel cascaded backbone-branches fully convolutional neural network~(BB-FCN) for rapidly and accurately localizing facial landmarks in unconstrained and cluttered settings.
no code implementations • NeurIPS 2018 • Yu Ji, Ling Liang, Lei Deng, Youyang Zhang, Youhui Zhang, Yuan Xie
Increasing the sparsity granularity can lead to better hardware utilization, but it will compromise the sparsity for maintaining accuracy.
no code implementations • NeurIPS 2018 • Peiqi Wang, Xinfeng Xie, Lei Deng, Guoqi Li, Dongsheng Wang, Yuan Xie
For example, we improve the perplexity per word (PPW) of a ternary LSTM on Penn Tree Bank (PTB) corpus from 126 (the state-of-the-art result to the best of our knowledge) to 110. 3 with a full precision model in 97. 2, and a ternary GRU from 142 to 113. 5 with a full precision model in 102. 7.
no code implementations • NeurIPS 2018 • Longquan Dai, Liang Tang, Yuan Xie, Jinhui Tang
Over the decades, people took a handmade approach to design fast algorithms for the Gaussian convolution.
no code implementations • 13 Nov 2018 • Shi-Yang Yan, Yuan Xie, Fang-Yu Wu, Jeremy S. Smith, Wenjin Lu, Bai-Ling Zhang
Automatically generating the descriptions of an image, i. e., image captioning, is an important and fundamental topic in artificial intelligence, which bridges the gap between computer vision and natural language processing.
no code implementations • 1 Nov 2018 • Xiaotong Luo, Rong Chen, Yuan Xie, Yanyun Qu, Cuihua Li
In this paper, motivated by [1], we aim to generate a high-quality SR result which balances between the two indices, i. e., the perception index and root-mean-square error (RMSE).
no code implementations • 25 Oct 2018 • Zhaodong Chen, Lei Deng, Guoqi Li, Jiawei Sun, Xing Hu, Xin Ma, Yuan Xie
In this paper, we propose alleviating this problem through sampling only a small fraction of data for normalization at each iteration.
no code implementations • ICLR 2019 • Liu Liu, Lei Deng, Xing Hu, Maohua Zhu, Guoqi Li, Yufei Ding, Yuan Xie
We propose to execute deep neural networks (DNNs) with dynamic and sparse graph (DSG) structure for compressive memory and accelerative execution during both training and inference.
no code implementations • 19 Aug 2018 • Bingqian Lin, Yuan Xie, Yanyun Qu, Cuihua Li, Xiaodan Liang
To our best knowledge, this is the first work to model the multi-view clustering in a deep joint framework, which will provide a meaningful thinking in unsupervised multi-view learning.
no code implementations • ICLR 2019 • Yuan Xie, Boyi Liu, Qiang Liu, Zhaoran Wang, Yuan Zhou, Jian Peng
Such an error reduction phenomenon is somewhat surprising as the estimated surrogate policy is less accurate than the given historical policy.
no code implementations • 25 Jul 2018 • Ling Liang, Lei Deng, Yueling Zeng, Xing Hu, Yu Ji, Xin Ma, Guoqi Li, Yuan Xie
Crossbar architecture based devices have been widely adopted in neural network accelerators by taking advantage of the high efficiency on vector-matrix multiplication (VMM) operations.
no code implementations • 1 Jun 2018 • Maohua Zhu, Jason Clemons, Jeff Pool, Minsoo Rhu, Stephen W. Keckler, Yuan Xie
Further, we can enforce structured sparsity in the gate gradients to make the LSTM backward pass up to 45% faster than the state-of-the-art dense approach and 168% faster than the state-of-the-art sparsifying method on modern GPUs.
no code implementations • CVPR 2018 • Guanbin Li, Yuan Xie, Tianhao Wei, Keze Wang, Liang Lin
Image saliency detection has recently witnessed significant progress due to deep convolutional neural networks.
Ranked #2 on Video Salient Object Detection on DAVSOD-Difficult20 (using extra training data)
no code implementations • 17 Mar 2018 • Guanbin Li, Yuan Xie, Liang Lin
Our algorithm is based on alternately exploiting a graphical model and training a fully convolutional network for model updating.
no code implementations • 27 Feb 2018 • Shuang Wu, Guoqi Li, Lei Deng, Liu Liu, Yuan Xie, Luping Shi
Batch Normalization (BN) has been proven to be quite effective at accelerating and improving the training of deep neural networks (DNNs).
no code implementations • 15 Nov 2017 • Yu Ji, Youhui Zhang, WenGuang Chen, Yuan Xie
Different from developing neural networks (NNs) for general-purpose processors, the development for NN chips usually faces with some hardware-specific restrictions, such as limited precision of network signals and parameters, constrained computation scale, and limited types of non-linear functions.
no code implementations • 27 Sep 2017 • Zhizhong Zhang, Yuan Xie, Wensheng Zhang, Qi Tian
In this paper, we propose a new multi-index fusion scheme for image retrieval.
no code implementations • 15 Sep 2017 • Yanyun Qu, Jinyan Liu, Yuan Xie, Wensheng Zhang
In particular, the original tensor-based multi-view self-representation clustering problem is a special case of our approach and can be solved by our algorithm.
no code implementations • 15 Sep 2017 • Yanyun Qu, Li Lin, Fumin Shen, Chang Lu, Yang Wu, Yuan Xie, DaCheng Tao
We propose a novel image classification method based on learning hierarchical inter-class structures.
no code implementations • CVPR 2017 • Guanbin Li, Yuan Xie, Liang Lin, Yizhou Yu
Image saliency detection has recently witnessed rapid progress due to deep convolutional neural networks.
Ranked #15 on RGB Salient Object Detection on DUTS-TE (max F-measure metric)
no code implementations • 23 Oct 2016 • Yuan Xie, DaCheng Tao, Wensheng Zhang, Lei Zhang, Yan Liu, Yanyun Qu
Different from traditional unfolding based tensor norm, this low-rank tensor constraint has optimality properties similar to that of matrix rank derived from SVD, so the complementary information among views can be explored more efficiently and thoroughly.
no code implementations • 20 Jun 2016 • Maohua Zhu, Liu Liu, Chao Wang, Yuan Xie
To improve the performance and maintain the scalability, we present CNNLab, a novel deep learning framework using GPU and FPGA-based accelerators.
no code implementations • 23 May 2016 • Chao Wang, Qi Yu, Lei Gong, Xi Li, Yuan Xie, Xuehai Zhou
As the emerging field of machine learning, deep learning shows excellent ability in solving complex learning problems.
no code implementations • 3 Dec 2015 • Yuan Xie, Shuhang Gu, Yan Liu, WangMeng Zuo, Wensheng Zhang, Lei Zhang
However, NNM tends to over-shrink the rank components and treats the different rank components equally, limiting its flexibility in practical applications.
no code implementations • 7 Sep 2015 • Wenrui Hu, DaCheng Tao, Wensheng Zhang, Yuan Xie, Yehui Yang
On the other, t-TNN is equal to the nuclear norm of block circulant matricization of the twist tensor in the original domain, which extends the traditional matrix nuclear norm in a block circulant way.
no code implementations • 7 Jan 2015 • Yuan Xie
An efficient algorithm is also proposed to solve the WSNM problem.
no code implementations • 17 Jan 2014 • Yuan Xie, Wensheng Zhang, DaCheng Tao, Wenrui Hu, Yanyun Qu, Hanzi Wang
To solve, or at least reduce these effects, we propose a new scheme to recover a latent image from observed frames by integrating a new variational model and distortion-driven spatial-temporal kernel regression.