Zobrazeno 1 - 10
of 969
pro vyhledávání: '"Zeng Long"'
Autor:
Cheng, Xi, Lei, Ruiqi, Huang, Di, Liao, Zhichao, Piao, Fengyuan, Chen, Yan, Feng, Pingfa, Zeng, Long
Parametric point clouds are sampled from CAD shapes, and have become increasingly prevalent in industrial manufacturing. However, most existing point cloud learning methods focus on the geometric features, such as developing efficient convolution ope
Externí odkaz:
http://arxiv.org/abs/2411.07747
Autor:
Liao, Zhichao, Huang, Di, Fang, Heming, Ma, Yue, Piao, Fengyuan, Li, Xinghui, Zeng, Long, Feng, Pingfa
Drawing freehand sketches of mechanical components on multimedia devices for AI-based engineering modeling has become a new trend. However, its development is being impeded because existing works cannot produce suitable sketches for data-driven resea
Externí odkaz:
http://arxiv.org/abs/2408.05966
Autor:
Yu, Jianxiang, Ding, Zichen, Tan, Jiaqi, Luo, Kangyang, Weng, Zhenmin, Gong, Chenghua, Zeng, Long, Cui, Renjing, Han, Chengcheng, Sun, Qiushi, Wu, Zhiyong, Lan, Yunshi, Li, Xiang
In recent years, the rapid increase in scientific papers has overwhelmed traditional review mechanisms, resulting in varying quality of publications. Although existing methods have explored the capabilities of Large Language Models (LLMs) for automat
Externí odkaz:
http://arxiv.org/abs/2407.12857
Autor:
Tang, Yifan, Tai, Cong, Chen, Fangxing, Zhang, Wanting, Zhang, Tao, Liu, Xueping, Liu, Yongjin, Zeng, Long
Publikováno v:
IEEE International Conference on Robotics & Automation,2024
Most existing robotic datasets capture static scene data and thus are limited in evaluating robots' dynamic performance. To address this, we present a mobile robot oriented large-scale indoor dataset, denoted as THUD (Tsinghua University Dynamic) rob
Externí odkaz:
http://arxiv.org/abs/2406.19791
In the present paper, we study the properties of $\phi$-meson longitudinal leading-twist light-cone distribution amplitude $\phi_{2;{\phi}}^{\|}(x,\mu)$ by starting from a light-cone harmonic oscillator model for its wavefunction. To fix the input pa
Externí odkaz:
http://arxiv.org/abs/2403.10003
Despite the success in 6D pose estimation in bin-picking scenarios, existing methods still struggle to produce accurate prediction results for symmetry objects and real world scenarios. The primary bottlenecks include 1) the ambiguity keypoints cause
Externí odkaz:
http://arxiv.org/abs/2403.09317
Existing Object Pose Estimation (OPE) methods for stacked scenarios are not robust to changes in object scale. This paper proposes a new 6DoF OPE network (NormNet) for different scale objects in stacked scenarios. Specifically, each object's scale is
Externí odkaz:
http://arxiv.org/abs/2311.09269
Autor:
Zeng, Long, Wu, Kaigui
Transformers have achieved significant success in medical image segmentation, owing to its capability to capture long-range dependencies. Previous works incorporate convolutional layers into the encoder module of transformers, thereby enhancing their
Externí odkaz:
http://arxiv.org/abs/2310.10957
Autor:
Ni, Zhe, Deng, Xiaoxin, Tai, Cong, Zhu, Xinyue, Xie, Qinghongbing, Huang, Weihang, Wu, Xiang, Zeng, Long
Recent works have shown that Large Language Models (LLMs) can facilitate the grounding of instructions for robotic task planning. Despite this progress, most existing works have primarily focused on utilizing raw images to aid LLMs in understanding e
Externí odkaz:
http://arxiv.org/abs/2309.07726
Publikováno v:
Eur. Phys. J. C 84 (2024) 15
The $\eta^{(\prime)}$-mesons in the quark-flavor basis are mixtures of two mesonic states $|\eta_{q}\rangle=|\bar u u+\bar d d\rangle/\sqrt 2$ and $|\eta_{s}\rangle=|\bar s s\rangle$. In the previous work, we have made a detailed study on the $\eta_{
Externí odkaz:
http://arxiv.org/abs/2307.04640