Zobrazeno 1 - 10
of 2 940
pro vyhledávání: '"Zhan, Wei"'
Autor:
Jacobson, Philip, Xie, Yichen, Ding, Mingyu, Xu, Chenfeng, Tomizuka, Masayoshi, Zhan, Wei, Wu, Ming C.
Semi-supervised 3D object detection is a common strategy employed to circumvent the challenge of manually labeling large-scale autonomous driving perception datasets. Pseudo-labeling approaches to semi-supervised learning adopt a teacher-student fram
Externí odkaz:
http://arxiv.org/abs/2409.10901
Robot exploration aims at constructing unknown environments and it is important to achieve it with shorter paths. Traditional methods focus on optimizing the visiting order based on current observations, which may lead to local-minimal results. Recen
Externí odkaz:
http://arxiv.org/abs/2409.10878
Autor:
Tang, Weiliang, Pan, Jia-Hui, Zhan, Wei, Zhou, Jianshu, Yao, Huaxiu, Liu, Yun-Hui, Tomizuka, Masayoshi, Ding, Mingyu, Fu, Chi-Wing
Observing that the key for robotic action planning is to understand the target-object motion when its associated part is manipulated by the end effector, we propose to generate the 3D object-part scene flow and extract its transformations to solve th
Externí odkaz:
http://arxiv.org/abs/2409.10032
We study the mass spectra and radiative decays of $D_{s0}^*(2317)$ and $D_{s1}^{\prime}(2460)$ in an unquenched framework. In addition to coupled channel effects between the $c\bar{s}$ cores and $D^{(*)}K$ channels, $D^{(*)}K$-$D^{(*)}K$ self interac
Externí odkaz:
http://arxiv.org/abs/2409.05337
Autor:
Zhang, Huixin, Wang, Guangming, Wu, Xinrui, Xu, Chenfeng, Ding, Mingyu, Tomizuka, Masayoshi, Zhan, Wei, Wang, Hesheng
This paper introduces a 3D point cloud sequence learning model based on inconsistent spatio-temporal propagation for LiDAR odometry, termed DSLO. It consists of a pyramid structure with a spatial information reuse strategy, a sequential pose initiali
Externí odkaz:
http://arxiv.org/abs/2409.00744
Autor:
Wang, Yixiao, Tang, Chen, Sun, Lingfeng, Rossi, Simone, Xie, Yichen, Peng, Chensheng, Hannagan, Thomas, Sabatini, Stefano, Poerio, Nicola, Tomizuka, Masayoshi, Zhan, Wei
Diffusion models are promising for joint trajectory prediction and controllable generation in autonomous driving, but they face challenges of inefficient inference steps and high computational demands. To tackle these challenges, we introduce Optimal
Externí odkaz:
http://arxiv.org/abs/2408.00766
We prove a Carbery-Wright style anti-concentration inequality for the unitary Haar measure, by showing that the probability of a polynomial in the entries of a random unitary falling into an $\varepsilon$ range is at most a polynomial in $\varepsilon
Externí odkaz:
http://arxiv.org/abs/2407.19561
We refine our previous calculation of multipole amplitude $E_{0+}$ for pion photo-production process, $\gamma N\rightarrow\pi N$. The treatment of final state interactions is based upon an earlier analysis of pion-nucleon scattering within Hamiltonia
Externí odkaz:
http://arxiv.org/abs/2407.05334
Autor:
Li, Yiheng, Ge, Chongjian, Li, Chenran, Xu, Chenfeng, Tomizuka, Masayoshi, Tang, Chen, Ding, Mingyu, Zhan, Wei
We propose Waymo Open Motion Dataset-Reasoning (WOMD-Reasoning), a language annotation dataset built on WOMD, with a focus on describing and reasoning interactions and intentions in driving scenarios. Previous language datasets primarily captured int
Externí odkaz:
http://arxiv.org/abs/2407.04281
Autor:
Wang, Yixiao, Zhang, Yifei, Huo, Mingxiao, Tian, Ran, Zhang, Xiang, Xie, Yichen, Xu, Chenfeng, Ji, Pengliang, Zhan, Wei, Ding, Mingyu, Tomizuka, Masayoshi
The increasing complexity of tasks in robotics demands efficient strategies for multitask and continual learning. Traditional models typically rely on a universal policy for all tasks, facing challenges such as high computational costs and catastroph
Externí odkaz:
http://arxiv.org/abs/2407.01531