no code implementations • 13 Nov 2024 • Zhimin Chen, Bing Li
Semi-supervised learning (SSL) leverages limited labeled and abundant unlabeled data but often faces challenges with data imbalance, especially in 3D contexts.
no code implementations • 16 Oct 2024 • Zhimin Chen, Liang Yang, Yingwei Li, Longlong Jing, Bing Li
Foundation models have significantly enhanced 2D task performance, and recent works like Bridge3D have successfully applied these models to improve 3D scene understanding through knowledge distillation, marking considerable advancements.
no code implementations • 16 Apr 2024 • Satya R. Jaladi, Zhimin Chen, Narahari R. Malayanur, Raja M. Macherla, Bing Li
The proposed solution is validated in GTA V games, and the results demonstrate the effectiveness of this end-to-end gamification framework for learning human driving skills.
1 code implementation • 17 Nov 2023 • Zhimin Chen, Yingwei Li, Longlong Jing, Liang Yang, Bing Li
However, a notable limitation of these approaches is that they do not fully utilize the multi-view attributes inherent in 3D point clouds, which is crucial for a deeper understanding of 3D structures.
no code implementations • 3 Oct 2023 • Vaibhav Bihani, Utkarsh Pratiush, Sajid Mannan, Tao Du, Zhimin Chen, Santiago Miret, Matthieu Micoulaut, Morten M Smedskjaer, Sayan Ranu, N M Anoop Krishnan
In addition to our thorough evaluation and analysis on eight existing datasets based on the benchmarking literature, we release two new benchmark datasets, propose four new metrics, and three challenging tasks.
Ranked #1 on
Formation Energy
on GeTe
1 code implementation • 25 Sep 2023 • Zhimin Chen, Peng Chen, Le Zheng, Yudong Zhang
After formulating the system model with the mutual coupling effect and the reflection phase/amplitude errors of the RIS, a novel DNNDANM method is proposed for the DOA estimation by combining the deep neural network (DNN) and the decoupling atomic norm minimization (DANM).
no code implementations • 13 Sep 2023 • Zhihang Ren, Jefferson Ortega, Yifan Wang, Zhimin Chen, Yunhui Guo, Stella X. Yu, David Whitney
Along with the dataset, we propose a new computer vision task to infer the affect of the selected character via both context and character information in each video frame.
1 code implementation • NeurIPS 2023 • Zhimin Chen, Longlong Jing, Yingwei Li, Bing Li
Foundation models have achieved remarkable results in 2D and language tasks like image segmentation, object detection, and visual-language understanding.
2 code implementations • 18 Oct 2022 • Zhimin Chen, Longlong Jing, Liang Yang, Yingwei Li, Bing Li
Firstly, a dynamic thresholding strategy is proposed to utilize more unlabeled data, especially for low learning status classes.
1 code implementation • 25 May 2022 • Peng Chen, Zhimin Chen, Pu Miao, Yun Chen
This letter addresses the passive sensing issue utilizing wireless communication signals and RIS amidst interference from wireless access points (APs).
1 code implementation • 25 Apr 2022 • Zhimin Chen, Peng Chen, Ziyu Guo, Yudong Zhang, Xianbin Wang
A novel estimation method is proposed in the scenario with a receiver using only one full-functional channel, where multiple measurements for the DOA estimation are achieved by controlling the reflection matrix (measurement matrix) in the RIS.
no code implementations • 19 Mar 2022 • Peng Chen, Zihan Yang, Zhimin Chen, Ziyu Guo
The direction of arrival (DOA) estimation problem is addressed in this letter.
2 code implementations • 19 Mar 2022 • Peng Chen, Zhimin Chen, Liang Liu, Yun Chen, Xianbin Wang
The estimation of direction of arrival (DOA) is a crucial issue in conventional radar, wireless communication, and integrated sensing and communication (ISAC) systems.
1 code implementation • 19 Mar 2022 • Peng Chen, Zhimin Chen, Beixiong Zheng, Xianbin Wang
Specifically, considering the position perturbation of UAVs, a new atomic norm-based DOA estimation method is proposed, where an atomic norm is defined with the parameter of the position perturbation.
1 code implementation • 22 Oct 2021 • Zhimin Chen, Longlong Jing, Yang Liang, YingLi Tian, Bing Li
This paper explores how the coherence of different modelities of 3D data (e. g. point cloud, image, and mesh) can be used to improve data efficiency for both 3D classification and retrieval tasks.
no code implementations • 29 Sep 2021 • Longlong Jing, Zhimin Chen, Bing Li, YingLi Tian
Our proposed novel self-supervised model learns two types of distinct features: modality-invariant features and modality-specific features.
no code implementations • 10 Jan 2020 • Kaushik Chakrabarti, Zhimin Chen, Siamak Shakeri, Guihong Cao
Tables extracted from web documents can be used to directly answer many web search queries.
no code implementations • 10 Jan 2020 • Kaushik Chakrabarti, Zhimin Chen, Siamak Shakeri, Guihong Cao, Surajit Chaudhuri
For (ii), we develop novel features to compute structure-aware match and train a machine learning model.
no code implementations • 5 Oct 2019 • Peng Chen, Zhimin Chen, Zhenxin Cao, Xianbin Wang
The problem of direction of arrival (DOA) estimation has been studied for decades as an essential technology in enabling radar, wireless communications, and array signal processing related applications.
no code implementations • 24 Jan 2019 • Zhimin Chen, Darius Parvin, Maedbh King, Susan Hao
Independent component analysis (ICA) has often been used as a tool to model natural image statistics by separating multivariate signals in the image into components that are assumed to be independent.
no code implementations • SEMEVAL 2018 • Zhimin Chen, Wei Song, Lizhen Liu
The task is to select the correct warrant that explains reasoning of a particular argument consisting of a claim and a reason.
no code implementations • 12 Apr 2018 • Peng Chen, Zhenxin Cao, Zhimin Chen, Xianbin Wang
With regard to the DOA estimation performance, the proposed SBLMC method can outperform state-of-the-art methods in the MIMO radar with unknown mutual coupling effect, while keeping the acceptable computational complexity.
2 code implementations • 6 May 2017 • Zhimin Chen, Yuguang Tong
Generative adversarial networks (GANs) have received a tremendous amount of attention in the past few years, and have inspired applications addressing a wide range of problems.