no code implementations • 17 Apr 2024 • Nawfal Guefrachi, Jian Shi, Hakim Ghazzai, Ahmad Alsharoa
The integration of Light Detection and Ranging (LiDAR) and Internet of Things (IoT) technologies offers transformative opportunities for public health informatics in urban safety and pedestrian well-being.
no code implementations • 16 Feb 2024 • Zirui Liao, Jian Shi, Yuwei Zhang, Shaoping Wang, Zhiyong Sun
Furthermore, miscellaneous resilient coordination problems are discussed in this survey.
no code implementations • 26 Jan 2024 • Lifu Zhang, Ji-An Li, Yang Hu, Jie Jiang, Rongjie Lai, Marcus K. Benna, Jian Shi
The memory consolidation from coupled storage components is revealed by both numerical simulations and experimental observations.
1 code implementation • 11 Dec 2023 • Jian Shi, Peter Wonka
To the best of our knowledge, \textit{VoxelKP} is the first single-staged, fully sparse network that is specifically designed for addressing the challenging task of 3D keypoint estimation from LiDAR data, achieving state-of-the-art performances.
Ranked #1 on 3D Human Pose Estimation on Waymo Open Dataset
no code implementations • 22 Oct 2023 • Tanhua Jin, Kailai Wang, Yanan Xin, Jian Shi, Ye Hong, Frank Witlox
Enhanced efforts in the transportation sector should be implemented to mitigate the adverse effects of CO2 emissions resulting from zoning-based planning paradigms.
no code implementations • 9 Apr 2023 • Jian Shi, Ni Zhang
In order to address the lack of abnormal data for robust anomaly detection, we propose Adversarial Generative Anomaly Detection (AGAD), a self-contrast-based anomaly detection paradigm that learns to detect anomalies by generating \textit{contextual adversarial information} from the massive normal examples.
Semi-supervised Anomaly Detection Supervised Anomaly Detection
1 code implementation • 28 Feb 2023 • Jian Shi, Pengyi Zhang, Ni Zhang, Hakim Ghazzai, Peter Wonka
In this paper, we introduce \textit{DIA}, dissolving is amplifying.
no code implementations • 9 Dec 2022 • Fatemeh Kalantari, Jian Shi, Harish Krishnamoorthy
This paper proposes a novel two-stage hybrid domain decomposition algorithm to speed up the dynamic simulations and the analysis of power systems that can be computationally demanding due to the high penetration of renewables.
no code implementations • 18 Oct 2022 • Yijie Yang, Jian Shi, Dan Wang, Chenye Wu, Zhu Han
Carbon emission markets can play a significant role in this transition by putting a price on carbon and giving electricity producers an incentive to reduce their emissions.
no code implementations • 17 Oct 2022 • Jian Shi, Dan Wang, Chenye Wu, Zhu Han
The retirement of unabated coal power plants, the plummeting cost of renewable energy technologies, along with more aggressive public policies and regulatory reforms, are occurring at an unprecedented speed to decarbonize the power and energy systems towards the 2030 and 2050 climate goals.
no code implementations • 12 Aug 2022 • Jian Shi, Baoli Sun, Xinchen Ye, Zhihui Wang, Xiaolong Luo, Jin Liu, Heli Gao, Haojie Li
Therefore, we propose a semantic decomposition network (SDNet) that introduces two single-task branches to separately address the segmentation of teeth and dental plaque and designs additional constraints to learn category-specific features for each branch, thus facilitating the semantic decomposition and improving the performance of dental plaque segmentation.
1 code implementation • 7 Apr 2022 • Anguelos Nicolaou, Vincent Christlein, Edgar Riba, Jian Shi, Georg Vogeler, Mathias Seuret
We propose the use of fractals as a means of efficient data augmentation.
Ranked #1 on No real Data Binarization on DIBCO and H_DIBCO 2009
no code implementations • 21 Mar 2022 • Cheng Zhang, Jian Shi, Xuan Deng, Zizhao Wu
In computer-aided design (CAD) community, the point cloud data is pervasively applied in reverse engineering, where the point cloud analysis plays an important role.
1 code implementation • TMM 2021 • Zhongqi Wu, Chuanqing Zhuang, Jian Shi, Jianwei Guo, Jun Xiao, Xiaopeng Zhang, Dong-Ming Yan
Specular reflections pose great challenges on various multimedia and computer vision tasks, e. g. , image segmentation, detection and matching.
1 code implementation • 19 Nov 2020 • Jian Shi, Edgar Riba, Dmytro Mishkin, Francesc Moreno, Anguelos Nicolaou
In this paper we present a review of the Kornia differentiable data augmentation (DDA) module for both for spatial (2D) and volumetric (3D) tensors.
no code implementations • 18 Jul 2019 • Ming Dong, Jian Shi, QingXin Shi
It was compared with traditional methods and our previous sequence prediction method.
1 code implementation • CVPR 2017 • Jian Shi, Yue Dong, Hao Su, Stella X. Yu
Rendered with realistic environment maps, millions of synthetic images of objects and their corresponding albedo, shading, and specular ground-truth images are used to train an encoder-decoder CNN.