Zobrazeno 1 - 10
of 1 370
pro vyhledávání: '"Zhang, HaiMing"'
This technical report summarizes the second-place solution for the Predictive World Model Challenge held at the CVPR-2024 Workshop on Foundation Models for Autonomous Systems. We introduce D$^2$-World, a novel World model that effectively forecasts f
Externí odkaz:
http://arxiv.org/abs/2411.17027
Autor:
Zhang, Haiming, Zhou, Wending, Zhu, Yiyao, Yan, Xu, Gao, Jiantao, Bai, Dongfeng, Cai, Yingjie, Liu, Bingbing, Cui, Shuguang, Li, Zhen
This paper introduces VisionPAD, a novel self-supervised pre-training paradigm designed for vision-centric algorithms in autonomous driving. In contrast to previous approaches that employ neural rendering with explicit depth supervision, VisionPAD ut
Externí odkaz:
http://arxiv.org/abs/2411.14716
Autor:
Zhou, Quan, Pei, Changhua, Sun, Fei, Han, Jing, Gao, Zhengwei, Pei, Dan, Zhang, Haiming, Xie, Gaogang, Li, Jianhui
Time series anomaly detection (TSAD) has become an essential component of large-scale cloud services and web systems because it can promptly identify anomalies, providing early warnings to prevent greater losses. Deep learning-based forecasting metho
Externí odkaz:
http://arxiv.org/abs/2411.00278
Autor:
Zhang, He-Shou, Ponti, Gabriele, Carretti, Ettore, Liu, Ruo-Yu, Morris, Mark R., Haverkorn, Marijke, Locatelli, Nicola, Zheng, Xueying, Aharonian, Felix, Zhang, Haiming, Zhang, Yi, Stel, Giovanni, Strong, Andrew, Yeung, Micheal, Merloni, Andrea
Publikováno v:
Nature Astronomy (2024)
Large-scale magnetic fields are observed off the midplanes of disk galaxies, indicating that they harbour magnetised halos. These halos are crucial to studies of galaxy evolution, galactic-scale outflows, and feedback from star formation activity. Id
Externí odkaz:
http://arxiv.org/abs/2408.06312
Autor:
Si, Haotian, Li, Jianhui, Pei, Changhua, Cui, Hang, Yang, Jingwen, Sun, Yongqian, Zhang, Shenglin, Li, Jingjing, Zhang, Haiming, Han, Jing, Pei, Dan, Xie, Gaogang
Time series anomaly detection (TSAD) has gained significant attention due to its real-world applications to improve the stability of modern software systems. However, there is no effective way to verify whether they can meet the requirements for real
Externí odkaz:
http://arxiv.org/abs/2402.10802
Autor:
Wang, Zexin, Pei, Changhua, Ma, Minghua, Wang, Xin, Li, Zhihan, Pei, Dan, Rajmohan, Saravan, Zhang, Dongmei, Lin, Qingwei, Zhang, Haiming, Li, Jianhui, Xie, Gaogang
Time series Anomaly Detection (AD) plays a crucial role for web systems. Various web systems rely on time series data to monitor and identify anomalies in real time, as well as to initiate diagnosis and remediation procedures. Variational Autoencoder
Externí odkaz:
http://arxiv.org/abs/2402.02820
Autor:
Zhang, Haiming, Yan, Xu, Bai, Dongfeng, Gao, Jiantao, Wang, Pan, Liu, Bingbing, Cui, Shuguang, Li, Zhen
3D occupancy prediction is an emerging task that aims to estimate the occupancy states and semantics of 3D scenes using multi-view images. However, image-based scene perception encounters significant challenges in achieving accurate prediction due to
Externí odkaz:
http://arxiv.org/abs/2312.11829
Autor:
Zhang, Haiming, Yuan, Zhihao, Zheng, Chaoda, Yan, Xu, Wang, Baoyuan, Li, Guanbin, Wu, Song, Cui, Shuguang, Li, Zhen
Although existing speech-driven talking face generation methods achieve significant progress, they are far from real-world application due to the avatar-specific training demand and unstable lip movements. To address the above issues, we propose the
Externí odkaz:
http://arxiv.org/abs/2312.07385
Autor:
Liu, Yuhe, Pei, Changhua, Xu, Longlong, Chen, Bohan, Sun, Mingze, Zhang, Zhirui, Sun, Yongqian, Zhang, Shenglin, Wang, Kun, Zhang, Haiming, Li, Jianhui, Xie, Gaogang, Wen, Xidao, Nie, Xiaohui, Ma, Minghua, Pei, Dan
Information Technology (IT) Operations (Ops), particularly Artificial Intelligence for IT Operations (AIOps), is the guarantee for maintaining the orderly and stable operation of existing information systems. According to Gartner's prediction, the us
Externí odkaz:
http://arxiv.org/abs/2310.07637
Autor:
Si, Haotian, Pei, Changhua, Li, Zhihan, Zhao, Yadong, Li, Jingjing, Zhang, Haiming, Diao, Zulong, Li, Jianhui, Xie, Gaogang, Pei, Dan
Massive key performance indicators (KPIs) are monitored as multivariate time series data (MTS) to ensure the reliability of the software applications and service system. Accurately detecting the abnormality of MTS is very critical for subsequent faul
Externí odkaz:
http://arxiv.org/abs/2308.08915