no code implementations • 14 Mar 2024 • Yuxuan Cai, Xinwei He, Dingkang Liang, Ao Tong, Xiang Bai
Recently, large vision and language models have shown their success when adapting them to many downstream tasks.
1 code implementation • 11 Oct 2023 • Yuxuan Cai, Dingkang Liang, Dongliang Luo, Xinwei He, Xin Yang, Xiang Bai
To alleviate this issue, we present a Discrepancy Aware Framework (DAF), which demonstrates robust performance consistently with simple and cheap strategies across different anomaly detection benchmarks.
1 code implementation • 12 May 2023 • Zhe Liu, Xiaoqing Ye, Zhikang Zou, Xinwei He, Xiao Tan, Errui Ding, Jingdong Wang, Xiang Bai
Extensive experiments on the nuScenes dataset demonstrate that our method is much more stable in dealing with challenging cases such as asynchronous sensors, misaligned sensor placement, and degenerated camera images than existing fusion methods.
Ranked #47 on 3D Object Detection on nuScenes
1 code implementation • 9 Dec 2021 • Silin Cheng, Xiwu Chen, Xinwei He, Zhe Liu, Xiang Bai
Learning intra-region contexts and inter-region relations are two effective strategies to strengthen feature representations for point cloud analysis.
Ranked #39 on 3D Point Cloud Classification on ModelNet40
no code implementations • 3 Sep 2021 • Xinwei He, Silin Cheng, Dingkang Liang, Song Bai, Xi Wang, Yingying Zhu
To investigate this, we propose a novel Locality-Aware Point-View Fusion Transformer (LATFormer) for 3D shape retrieval and classification.
2 code implementations • 19 Jul 2021 • Guoping Xu, Xingrong Wu, Xuan Zhang, Xinwei He
Medical image segmentation plays an essential role in developing computer-assisted diagnosis and therapy systems, yet still faces many challenges.
1 code implementation • 4 Sep 2019 • Yu Shi, Jiaming Shen, Yuchen Li, Naijing Zhang, Xinwei He, Zhengzhi Lou, Qi Zhu, Matthew Walker, Myunghwan Kim, Jiawei Han
Extensive experiments on two large real-world datasets demonstrate the effectiveness of HyperMine and the utility of modeling context granularity.
no code implementations • ICCV 2019 • Xinwei He, Tengteng Huang, Song Bai, Xiang Bai
By doing so, spatial information across multiple views is captured, which helps to learn a discriminative global embedding for each 3D object.
no code implementations • 21 Apr 2019 • Feng Yin, Lishuo Pan, Xinwei He, Tianshi Chen, Sergios Theodoridis, Zhi-Quan, Luo
Gaussian processes (GP) for machine learning have been studied systematically over the past two decades and they are by now widely used in a number of diverse applications.
1 code implementation • 28 Nov 2018 • Yu Shi, Xinwei He, Naijing Zhang, Carl Yang, Jiawei Han
We therefore approach the problem of user-guided clustering in HINs with network motifs.
1 code implementation • 29 Apr 2018 • Jiaming Shen, Jinfeng Xiao, Xinwei He, Jingbo Shang, Saurabh Sinha, Jiawei Han
Different from Web or general domain search, a large portion of queries in scientific literature search are entity-set queries, that is, multiple entities of possibly different types.
1 code implementation • CVPR 2018 • Xinwei He, Yang Zhou, Zhichao Zhou, Song Bai, Xiang Bai
Most existing 3D object recognition algorithms focus on leveraging the strong discriminative power of deep learning models with softmax loss for the classification of 3D data, while learning discriminative features with deep metric learning for 3D object retrieval is more or less neglected.
1 code implementation • 19 Jan 2018 • Yu Shi, Fangqiu Han, Xinwei He, Xinran He, Carl Yang, Jie Luo, Jiawei Han
With experiments on a series of synthetic datasets, a large-scale internal Snapchat dataset, and two public datasets, we confirm the validity and importance of preservation and collaboration as two objectives for multi-view network embedding.