no code implementations • 23 Mar 2023 • Mingze Wei, Yaomin Huang, Zhiyuan Xu, Ning Liu, Zhengping Che, Xinyu Zhang, Chaomin Shen, Feifei Feng, Chun Shan, Jian Tang
Our work significantly outperforms the state-of-the-art for three-finger robotic hands.
no code implementations • 23 Mar 2023 • Yaomin Huang, Ning Liu, Zhengping Che, Zhiyuan Xu, Chaomin Shen, Yaxin Peng, Guixu Zhang, Xinmei Liu, Feifei Feng, Jian Tang
CP$^3$ is elaborately designed to leverage the characteristics of point clouds and PNNs in order to enable 2D channel pruning methods for PNNs.
1 code implementation • 24 Jul 2022 • Yaomin Huang, Xinmei Liu, Yichen Zhu, Zhiyuan Xu, Chaomin Shen, Zhengping Che, Guixu Zhang, Yaxin Peng, Feifei Feng, Jian Tang
Detecting 3D objects from point clouds is a practical yet challenging task that has attracted increasing attention recently.
1 code implementation • Proceedings of the AAAI Conference on Artificial Intelligence 2022 • Sirisha Rambhatla, Zhengping Che, Yan Liu
To this end, we develop an Importance Sampling based distance metric -- I-SEA -- which enjoys the properties of a metric while consistently achieving superior performance for machine learning tasks such as classification and representation learning.
no code implementations • CVPR 2022 • Haowen Wang, Mingyuan Wang, Zhengping Che, Zhiyuan Xu, XIUQUAN QIAO, Mengshi Qi, Feifei Feng, Jian Tang
In this paper, we design a novel two-branch end-to-end fusion network, which takes a pair of RGB and incomplete depth images as input to predict a dense and completed depth map.
1 code implementation • 17 Feb 2022 • Yinuo Zhao, Kun Wu, Zhiyuan Xu, Zhengping Che, Qi Lu, Jian Tang, Chi Harold Liu
Vision-based autonomous urban driving in dense traffic is quite challenging due to the complicated urban environment and the dynamics of the driving behaviors.
no code implementations • 21 Oct 2021 • Wenzheng Hu, Ning Liu, Zhengping Che, Mingyang Li, Jian Tang, ChangShui Zhang, Jianqiang Wang
Deep convolutional neural networks are shown to be overkill with high parametric and computational redundancy in many application scenarios, and an increasing number of works have explored model pruning to obtain lightweight and efficient networks.
no code implementations • 23 Jul 2021 • Kun Wu, Chengxiang Yin, Zhengping Che, Bo Jiang, Jian Tang, Zheng Guan, Gangyi Ding
Deep generative models have made great progress in synthesizing images with arbitrary human poses and transferring poses of one person to others.
no code implementations • 19 Feb 2021 • Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang
In deep model compression, the recent finding "Lottery Ticket Hypothesis" (LTH) (Frankle & Carbin, 2018) pointed out that there could exist a winning ticket (i. e., a properly pruned sub-network together with original weight initialization) that can achieve competitive performance than the original dense network.
no code implementations • ICCV 2021 • Chengxiang Yin, Kun Wu, Zhengping Che, Bo Jiang, Zhiyuan Xu, Jian Tang
Deep learning has made tremendous success in computer vision, natural language processing and even visual-semantic learning, which requires a huge amount of labeled training data.
no code implementations • 5 Nov 2020 • Yue Shi, Bo Jiang, Zhengping Che, Jian Tang
In this work, we present a novel module, the Fluff block, to alleviate drawbacks of current multi-scale fusion methods and facilitate multi-scale object detection.
no code implementations • 5 Nov 2020 • Xuanzhao Wang, Zhengping Che, Bo Jiang, Ning Xiao, Ke Yang, Jian Tang, Jieping Ye, Jingyu Wang, Qi Qi
In this paper, we propose a novel and robust unsupervised video anomaly detection method by frame prediction with proper design which is more in line with the characteristics of surveillance videos.
no code implementations • 4 Nov 2020 • Yushuo Guan, Ning Liu, Pengyu Zhao, Zhengping Che, Kaigui Bian, Yanzhi Wang, Jian Tang
The convolutional neural network has achieved great success in fulfilling computer vision tasks despite large computation overhead against efficient deployment.
1 code implementation • NeurIPS 2020 • Zhiyuan Xu, Kun Wu, Zhengping Che, Jian Tang, Jieping Ye
While Deep Reinforcement Learning (DRL) has emerged as a promising approach to many complex tasks, it remains challenging to train a single DRL agent that is capable of undertaking multiple different continuous control tasks.
no code implementations • 3 Apr 2019 • Zhengping Che, Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, Jieping Ye
Driving datasets accelerate the development of intelligent driving and related computer vision technologies, while substantial and detailed annotations serve as fuels and powers to boost the efficacy of such datasets to improve learning-based models.
no code implementations • ICML 2018 • Zhengping Che, Sanjay Purushotham, Guangyu Li, Bo Jiang, Yan Liu
Multi-Rate Multivariate Time Series (MR-MTS) are the multivariate time series observations which come with various sampling rates and encode multiple temporal dependencies.
no code implementations • ICLR 2018 • Sanjay Purushotham, Zhengping Che, Bo Jiang, Tanachat Nilanon, Yan Liu
Recent advances in computing technology and sensor design have made it easier to collect longitudinal or time series data from patients, resulting in a gigantic amount of available medical data.
1 code implementation • 23 Oct 2017 • Sanjay Purushotham, Chuizheng Meng, Zhengping Che, Yan Liu
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications.
no code implementations • 6 Sep 2017 • Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, Yan Liu
We use this generative model together with a convolutional neural network (CNN) based prediction model to improve the onset prediction performance.
no code implementations • 25 Jan 2017 • Zhengping Che, Yu Cheng, Zhaonan Sun, Yan Liu
To account for high dimensionality, we use the embedding medical features in the CNN model which hold the natural medical concepts.
6 code implementations • 6 Jun 2016 • Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag, Yan Liu
Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values.
Ranked #4 on Multivariate Time Series Forecasting on MuJoCo
Multivariate Time Series Forecasting Multivariate Time Series Imputation +2
no code implementations • 11 Dec 2015 • Zhengping Che, Sanjay Purushotham, Robinder Khemani, Yan Liu
Exponential growth in Electronic Healthcare Records (EHR) has resulted in new opportunities and urgent needs for discovery of meaningful data-driven representations and patterns of diseases in Computational Phenotyping research.