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1,259 results on '"Wu, Haitao"'

1. Semantic Object-level Modeling for Robust Visual Camera Relocalization

Author

Zhu, Yifan, Miao, Lingjuan, Wu, Haitao, Zhou, Zhiqiang, Chen, Weiyi, and Wu, Longwen

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Robotics
Abstract

Visual relocalization is crucial for autonomous visual localization and navigation of mobile robotics. Due to the improvement of CNN-based object detection algorithm, the robustness of visual relocalization is greatly enhanced especially in viewpoints where classical methods fail. However, ellipsoids (quadrics) generated by axis-aligned object detection may limit the accuracy of the object-level representation and degenerate the performance of visual relocalization system. In this paper, we propose a novel method of automatic object-level voxel modeling for accurate ellipsoidal representations of objects. As for visual relocalization, we design a better pose optimization strategy for camera pose recovery, to fully utilize the projection characteristics of 2D fitted ellipses and the 3D accurate ellipsoids. All of these modules are entirely intergrated into visual SLAM system. Experimental results show that our semantic object-level mapping and object-based visual relocalization methods significantly enhance the performance of visual relocalization in terms of robustness to new viewpoints.

Published
2024

2. Unleashing the Power of Clippy in Real-World Rust Projects

Author

Li, Chunmiao, Yu, Yijun, Wu, Haitao, Carlig, Luca, Nie, Shijie, and Jiang, Lingxiao

Subjects
Computer Science - Software Engineering
Abstract

Clippy lints are considered as essential tools for Rust developers, as they can be configured as gate-keeping rules for a Rust project during continuous integration. Despite their availability, little was known about practical application and cost-effectiveness of the lints in reducing code quality issues. In this study, we embark on a comprehensive analysis to unveil the true impact of Clippy lints in the Rust development landscape. The study is structured around three interrelated components, each contributing to the overall effectiveness of Clippy. Firstly, we conduct a comprehensive analysis of Clippy lints in all idiomatic crates-io Rust projects with an average warning density of 21/KLOC. The analysis identifies the most cost-effective lint fixes, offering valuable opportunities for optimizing code quality. Secondly, we actively engage Rust developers through a user survey to garner invaluable feedback on their experiences with Clippy. User insights shed light on two crucial concerns: the prevalence of false positives in warnings and the need for auto-fix support for most warnings. Thirdly, building upon these findings, we engineer three innovative automated refactoring techniques to effectively fix the four most frequent Clippy lints. As a result, the warning density in Rosetta benchmarks has significantly decreased from 195/KLOC to an impressive 18/KLOC, already lower than the average density of the crates-io Rust projects. These results demonstrate tangible benefit and impact of our efforts in enhancing the overall code quality and maintainability for Rust developers.

Published
2023

5. Provable Dynamic Fusion for Low-Quality Multimodal Data

Author

Zhang, Qingyang, Wu, Haitao, Zhang, Changqing, Hu, Qinghua, Fu, Huazhu, Zhou, Joey Tianyi, and Peng, Xi

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition
Abstract

The inherent challenge of multimodal fusion is to precisely capture the cross-modal correlation and flexibly conduct cross-modal interaction. To fully release the value of each modality and mitigate the influence of low-quality multimodal data, dynamic multimodal fusion emerges as a promising learning paradigm. Despite its widespread use, theoretical justifications in this field are still notably lacking. Can we design a provably robust multimodal fusion method? This paper provides theoretical understandings to answer this question under a most popular multimodal fusion framework from the generalization perspective. We proceed to reveal that several uncertainty estimation solutions are naturally available to achieve robust multimodal fusion. Then a novel multimodal fusion framework termed Quality-aware Multimodal Fusion (QMF) is proposed, which can improve the performance in terms of classification accuracy and model robustness. Extensive experimental results on multiple benchmarks can support our findings., Comment: Accepted by ICML 2023

Published
2023

38. TNF-α and IL-8 levels are positively correlated with hypobaric hypoxic pulmonary hypertension and pulmonary vascular remodeling in rats

Author

Shi Haixia, Zhao Yongfeng, Li Su, Wu Haitao, Ma Dehua, and Wan Chenchen

Subjects
pulmonary arterial hypertension, tnf-α, mean pulmonary arterial pressure, pulmonary vascular remodeling, Biology (General), QH301-705.5
Abstract

The expression status of proinflammatory cytokines in high-altitude pulmonary arterial hypertension (PAH) has been well studied. However, the changes in interleukin (IL)-8 and tumor necrosis factor α (TNF-α) during the reversible changes in pulmonary vascular remodeling (PVR) in PAH after detaching from a hypobaric hypoxic environment have not been elucidated. This investigation elucidated a high-altitude PAH rat model. Then, PAH rats in the high-altitude group were maintained in the high-altitude area, and rats in the low-altitude group returned to the low-altitude area. After 0, 10, 20, and 30 days of PAH modeling, right ventricular systolic pressure (RVSP) and the mean pulmonary arterial pressure (mPAP) were assessed. Right ventricular (RV) hypertrophy was reflected by the ratio of RV/[left ventricle + interventricular septum (S)]. Pathological changes in PVR were accessed by hematoxylin-eosin staining, and medial wall thickness (WT%) and medial wall area (WA%) were measured. TNF-α and IL-8 levels in pulmonary artery tissues and blood were measured with Western blot assay and enzyme-linked immunosorbent assay, respectively. Our results showed that PAH rats exhibited a substantial increase in RVSP and mPAP, RV hypertrophy, PVR, and enhanced generation of TNF-α and IL-8. Then, we found that these pathological changes were gradually aggravated and TNF-α and IL-8 levels were increased in rats in the high-altitude group after 10, 20, and 30 days of PAH modeling. In contrast, the mPAP was decreased and PVR was alleviated in rats in the low-altitude group, accompanying with reduced TNF-α and IL-8 production. In conclusion, our study demonstrated that the generation of TNF-α and IL-8 was also reversible during the reversible changes in PVR after detaching from a hypobaric hypoxic environment. Thus, proinflammatory cytokine TNF-α and IL-8 levels are positively correlated with PVR severity.

Published
2023
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