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49,989 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

3. 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

10. 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

37. Photoluminescence studies of the charge states of nitrogen vacancy centers in diamond after arsenic ion implantation and subsequent annealing.

Author

Huangfu, Chenyang, Zhang, Yufei, Hao, Jinchen, Jia, Gangyuan, Wu, Haitao, Wang, Xujie, Wang, Wei, and Wang, Kaiyue

Subjects
ION implantation, ARSENIC, ELECTRON-hole recombination, ELECTRON-phonon interactions, DIAMONDS, REDSHIFT
Abstract

In this work, nitrogen vacancy (NV) centers of high nitrogen diamond implanted with arsenic ions were investigated by photoluminescence spectroscopy. The transition of the NV center charge state was discussed by the regularly changing laser excitation power and measurement temperature following high-temperature annealing. After high-temperature annealing, the amorphous layer generated by arsenic ion implantation is transformed into a graphitization layer, resulting in a decrease in the NV yield. The electric neutral NV (NV0) center and negatively charged NV (NV−) center are affected by both radiation recombination and Auger recombination with increasing laser power. Accompanied by the increasing measurement temperature, the intensities of NV centers gradually decreased and eventually quenched. In addition, the charge states of NV− and NV0 centers were undergoing a transition. The zero phonon line positions of NV centers were also red shift, it was attributed to the dominant role of electron–phonon interaction in the temperature-dependent displacement of diamond energy gaps. The full width at half maxima of NV center were broadened significantly at higher temperatures. [ABSTRACT FROM AUTHOR]

Published
2024
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