1 code implementation • ECCV 2020 • Miao Zhang, Sun Xiao Fei, Jie Liu, Shuang Xu, Yongri Piao, Huchuan Lu
In this paper, we propose an asymmetric two-stream architecture taking account of the inherent differences between RGB and depth data for saliency detection.
no code implementations • 21 Jun 2022 • Guanghao Li, Yue Hu, Miao Zhang, Ji Liu, Quanjun Yin, Yong Peng, Dejing Dou
As the efficiency of training in the ring topology prefers devices with homogeneous resources, the classification based on the computing capacity mitigates the impact of straggler effects.
no code implementations • 5 May 2022 • Hairun Xie, Jing Wang, Miao Zhang
The hard constrained scheme tend to generate and explore airfoils in a wider range for both geometry space and objective space, and the distribution in objective space is closer to normal distribution.
no code implementations • 9 Apr 2022 • Miao Zhang, Harvineet Singh, Lazarus Chok, Rumi Chunara
This work highlights the need to conduct fairness analysis for satellite imagery segmentation models and motivates the development of methods for fair transfer learning in order not to introduce disparities between places, particularly urban and rural locations.
no code implementations • 14 Feb 2022 • Xin Zheng, Yixin Liu, Shirui Pan, Miao Zhang, Di Jin, Philip S. Yu
Recent years have witnessed fast developments of graph neural networks (GNNs) that have benefited myriads of graph analytic tasks and applications.
1 code implementation • ICCV 2021 • Yongri Piao, Jian Wang, Miao Zhang, Huchuan Lu
The multiple accurate cues from multiple DFs are then simultaneously propagated to the saliency network with a multi-guidance loss.
1 code implementation • NeurIPS 2021 • Jingjing Li, Wei Ji, Qi Bi, Cheng Yan, Miao Zhang, Yongri Piao, Huchuan Lu, Li Cheng
As a by-product, a CapS dataset is constructed by augmenting existing benchmark training set with additional image tags and captions.
no code implementations • CVPR 2022 • Miao Zhang, Jilin Hu, Steven Su, Shirui Pan, Xiaojun Chang, Bin Yang, Gholamreza Haffari
Differentiable Architecture Search (DARTS) has received massive attention in recent years, mainly because it significantly reduces the computational cost through weight sharing and continuous relaxation.
no code implementations • 30 Oct 2021 • Miao Zhang, Miaojing Shi, Li Li
Last, to enhance the embedding space learning, an additional pixel-wise metric learning module is introduced with triplet loss formulated on the pixel-level embedding of the input image.
no code implementations • 8 Oct 2021 • Shengran Hu, Ran Cheng, Cheng He, Zhichao Lu, Jing Wang, Miao Zhang
For the goal of automated design of high-performance deep convolutional neural networks (CNNs), Neural Architecture Search (NAS) methodology is becoming increasingly important for both academia and industries. Due to the costly stochastic gradient descent (SGD) training of CNNs for performance evaluation, most existing NAS methods are computationally expensive for real-world deployments.
no code implementations • 4 Sep 2021 • Yongri Piao, Jian Wang, Miao Zhang, Zhengxuan Ma, Huchuan Lu
Despite of the success of previous works, explorations on an effective training strategy for the saliency network and accurate matches between image-level annotations and salient objects are still inadequate.
1 code implementation • 6 Jul 2021 • Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin
In this study, we propose a novel heterogeneity-aware federated learning method, SplitAVG, to overcome the performance drops from data heterogeneity in federated learning.
no code implementations • 24 Jun 2021 • Liangqiong Qu, Niranjan Balachandar, Miao Zhang, Daniel Rubin
Specifically, instead of directly training a model for task performance, we develop a novel dual model architecture: a primary model learns the desired task, and an auxiliary "generative replay model" allows aggregating knowledge from the heterogenous clients.
no code implementations • 22 Jun 2021 • Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Wei Huang, Bin Yang, Gholamreza Haffari
Although Differentiable ARchiTecture Search (DARTS) has become the mainstream paradigm in Neural Architecture Search (NAS) due to its simplicity and efficiency, more recent works found that the performance of the searched architecture barely increases with the optimization proceeding in DARTS, and the final magnitudes obtained by DARTS could hardly indicate the importance of operations.
1 code implementation • 21 Jun 2021 • Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Ehsan Abbasnejad, Reza Haffari
A key challenge to the scalability and quality of the learned architectures is the need for differentiating through the inner-loop optimisation.
1 code implementation • CVPR 2021 • Wei Ji, Jingjing Li, Shuang Yu, Miao Zhang, Yongri Piao, Shunyu Yao, Qi Bi, Kai Ma, Yefeng Zheng, Huchuan Lu, Li Cheng
Complex backgrounds and similar appearances between objects and their surroundings are generally recognized as challenging scenarios in Salient Object Detection (SOD).
no code implementations • 13 Apr 2021 • Yongri Piao, Yukun Zhang, Miao Zhang, Xinxin Ji
Focus based methods have shown promising results for the task of depth estimation.
1 code implementation • 13 Apr 2021 • Yongri Piao, Xinxin Ji, Miao Zhang, Yukun Zhang
We first excavate the internal spatial correlation by designing a context reasoning unit which separately extracts comprehensive contextual information from the focal stack and RGB images.
no code implementations • 19 Mar 2021 • Zheng Chu, Zhengyu Zhu, Miao Zhang, Fuhui Zhou, Li Zhen, Xueqian Fu, and Naofal Al-Dhahir
To evaluate the performance of this IRS assisted WPSN, we are interested in maximizing its system sum throughput to jointly optimize the energy beamforming of the PS, the transmission time allocation, as well as the phase shifts of the WET and WIT phases.
no code implementations • ICLR 2022 • Wei Huang, Yayong Li, Weitao Du, Jie Yin, Richard Yi Da Xu, Ling Chen, Miao Zhang
Inspired by our theoretical insights on trainability, we propose Critical DropEdge, a connectivity-aware and graph-adaptive sampling method, to alleviate the exponential decay problem more fundamentally.
1 code implementation • ICCV 2021 • Miao Zhang, Jie Liu, Yifei Wang, Yongri Piao, Shunyu Yao, Wei Ji, Jingjing Li, Huchuan Lu, Zhongxuan Luo
Our bidirectional dynamic fusion strategy encourages the interaction of spatial and temporal information in a dynamic manner.
Ranked #13 on
Video Polyp Segmentation
on SUN-SEG-Easy (Unseen)
no code implementations • 30 Dec 2020 • Yongri Piao, Zhengkun Rong, Shuang Xu, Miao Zhang, Huchuan Lu
The success of learning-based light field saliency detection is heavily dependent on how a comprehensive dataset can be constructed for higher generalizability of models, how high dimensional light field data can be effectively exploited, and how a flexible model can be designed to achieve versatility for desktop computers and mobile devices.
1 code implementation • NeurIPS 2020 • Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, ZongYuan Ge, Steven Su
A probabilistic exploration enhancement method is accordingly devised to encourage intelligent exploration during the architecture search in the latent space, to avoid local optimal in architecture search.
1 code implementation • 19 Oct 2020 • Jie Lian, Jingyu Liu, Yizhou Yu, Mengyuan Ding, Yaoci Lu, Yi Lu, Jie Cai, Deshou Lin, Miao Zhang, Zhe Wang, Kai He, Yijie Yu
The detection of thoracic abnormalities challenge is organized by the Deepwise AI Lab.
no code implementations • 3 Sep 2020 • Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard White, Behrooz Hashemian, Thomas Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina V. Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel Rubin, Jayashree Kalpathy-Cramer
Building robust deep learning-based models requires large quantities of diverse training data.
2 code implementations • ECCV 2020 • Wei Ji, Jingjing Li, Miao Zhang, Yongri Piao, Huchuan Lu
The explicitly extracted edge information goes together with saliency to give more emphasis to the salient regions and object boundaries.
Ranked #18 on
RGB-D Salient Object Detection
on NJU2K
no code implementations • 2 Jun 2020 • Xiong Zhang, Miao Zhang, Xiao Tian
Earthquake early warning systems are required to report earthquake locations and magnitudes as quickly as possible before the damaging S wave arrival to mitigate seismic hazards.
1 code implementation • CVPR 2020 • Miao Zhang, Weisong Ren, Yongri Piao, Zhengkun Rong, Huchuan Lu
Depth data containing a preponderance of discriminative power in location have been proven beneficial for accurate saliency prediction.
Ranked #14 on
RGB-D Salient Object Detection
on NJU2K
(using extra training data)
1 code implementation • CVPR 2020 • Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, Steven Su
In this paper, we formulate the supernet training in the One-Shot NAS as a constrained optimization problem of continual learning that the learning of current architecture should not degrade the performance of previous architectures during the supernet training.
2 code implementations • 22 Apr 2020 • Shuting He, Hao Luo, Weihua Chen, Miao Zhang, Yuqi Zhang, Fan Wang, Hao Li, Wei Jiang
Our solution is based on a strong baseline with bag of tricks (BoT-BS) proposed in person ReID.
1 code implementation • NeurIPS 2019 • Miao Zhang, Jingjing Li, Ji Wei, Yongri Piao, Huchuan Lu
In this paper, we present a deep-learning-based method where a novel memory-oriented decoder is tailored for light field saliency detection.
no code implementations • 22 Jul 2019 • Miao Zhang, Huiqi Li, Shirui Pan, Taoping Liu, Steven Su
The best architecture obtained by our algorithm with the same search space achieves the state-of-the-art test error rate of 2. 51\% on CIFAR-10 with only 7. 5 hours search time in a single GPU, and a validation perplexity of 60. 02 and a test perplexity of 57. 36 on PTB.
1 code implementation • 21 Jul 2019 • Miao Zhang, Huiqi Li, Steven Su
Furthermore, a kernel trick is developed to reduce computational complexity and learn nonlinear subset of the unknowing function when applying SIR to extremely high dimensional BO.
1 code implementation • 2 Jan 2019 • Tingting Qiao, Weijing Zhang, Miao Zhang, Zixuan Ma, Duanqing Xu
By doing so, the ancient painting processing problems become natural image processing problems and models trained on natural images can be directly applied to the transferred paintings.
1 code implementation • 2 Jan 2019 • Miao Zhang, Huiqi Li, Juan Lyu, Sai Ho Ling, Steven Su
In this paper, a non-stationary kernel is proposed which allows the surrogate model to adapt to functions whose smoothness varies with the spatial location of inputs, and a multi-level convolutional neural network (ML-CNN) is built for lung nodule classification whose hyperparameter configuration is optimized by using the proposed non-stationary kernel based Gaussian surrogate model.
no code implementations • 18 Mar 2018 • Xin Zhang, Bingfang Wu, Liang Zhu, Fuyou Tian, Miao Zhang, Yuanzeng
In this paper, we first test the state of the art semantic segmentation deep learning classifiers for LUCC mapping with 7 categories in the TGRA area with rapideye 5m resolution data.
no code implementations • 15 Nov 2017 • Miao Zhang, Xiaofei Kang, Yanqing Wang, Lantian Li, Zhiyuan Tang, Haisheng Dai, Dong Wang
Trivial events are ubiquitous in human to human conversations, e. g., cough, laugh and sniff.
1 code implementation • PLOS ONE 2017 • Xinyu Yang, Guoai Xu, Qi Li, Yanhui Guo, Miao Zhang
Then these metrics are input to neural network for supervised learning, the weights of which are output by PSO and BP hybrid algorithm.
no code implementations • 22 Jun 2017 • Miao Zhang, Yixiang Chen, Lantian Li, Dong Wang
This paper proposes a speaker recognition (SRE) task with trivial speech events, such as cough and laugh.