Zobrazeno 1 - 10
of 408
pro vyhledávání: '"Zhou, Bolei"'
Understanding and modeling pedestrian movements in the real world is crucial for applications like motion forecasting and scene simulation. Many factors influence pedestrian movements, such as scene context, individual characteristics, and goals, whi
Externí odkaz:
http://arxiv.org/abs/2410.07500
The rapid development of artificial intelligence (AI) has unearthed the potential to assist humans in controlling advanced technologies. Shared autonomy (SA) facilitates control by combining inputs from a human pilot and an AI copilot. In prior SA st
Externí odkaz:
http://arxiv.org/abs/2409.15317
Existing Vehicle-to-Everything (V2X) cooperative perception methods rely on accurate multi-agent 3D annotations. Nevertheless, it is time-consuming and expensive to collect and annotate real-world data, especially for V2X systems. In this paper, we p
Externí odkaz:
http://arxiv.org/abs/2408.11241
Autor:
Wu, Wayne, He, Honglin, He, Jack, Wang, Yiran, Duan, Chenda, Liu, Zhizheng, Li, Quanyi, Zhou, Bolei
Public urban spaces like streetscapes and plazas serve residents and accommodate social life in all its vibrant variations. Recent advances in Robotics and Embodied AI make public urban spaces no longer exclusive to humans. Food delivery bots and ele
Externí odkaz:
http://arxiv.org/abs/2407.08725
Autor:
Zhou, Yunsong, Simon, Michael, Peng, Zhenghao, Mo, Sicheng, Zhu, Hongzi, Guo, Minyi, Zhou, Bolei
Controllable synthetic data generation can substantially lower the annotation cost of training data. Prior works use diffusion models to generate driving images conditioned on the 3D object layout. However, those models are trained on small-scale dat
Externí odkaz:
http://arxiv.org/abs/2406.09386
Recent controllable generation approaches such as FreeControl and Diffusion Self-guidance bring fine-grained spatial and appearance control to text-to-image (T2I) diffusion models without training auxiliary modules. However, these methods optimize th
Externí odkaz:
http://arxiv.org/abs/2406.07540
Autor:
Zhang, Qihang, Xu, Yinghao, Wang, Chaoyang, Lee, Hsin-Ying, Wetzstein, Gordon, Zhou, Bolei, Yang, Ceyuan
Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This results in a lack of a unified approach to effectively control and ma
Externí odkaz:
http://arxiv.org/abs/2405.18424
Generating unbounded 3D scenes is crucial for large-scale scene understanding and simulation. Urban scenes, unlike natural landscapes, consist of various complex man-made objects and structures such as roads, traffic signs, vehicles, and buildings. T
Externí odkaz:
http://arxiv.org/abs/2403.11697
Traffic signal control (TSC) is crucial for reducing traffic congestion that leads to smoother traffic flow, reduced idling time, and mitigated CO2 emissions. In this study, we explore the computer vision approach for TSC that modulates on-road traff
Externí odkaz:
http://arxiv.org/abs/2403.06884
Autor:
Liu, Shengchao, Wang, Chengpeng, Lu, Jiarui, Nie, Weili, Wang, Hanchen, Li, Zhuoxinran, Zhou, Bolei, Tang, Jian
Deep generative models (DGMs) have been widely developed for graph data. However, much less investigation has been carried out on understanding the latent space of such pretrained graph DGMs. These understandings possess the potential to provide cons
Externí odkaz:
http://arxiv.org/abs/2401.17123