Zobrazeno 1 - 10
of 264
pro vyhledávání: '"Zhou, Bolei"'
Autor:
Wu, Wayne, He, Honglin, Wang, Yiran, Duan, Chenda, He, Jack, 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 in autonomous driving research and development. Prior works use diffusion models to generate driving images conditioned on the 3D object layout. Howev
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
Autor:
Zhang, Qihang, Wang, Chaoyang, Siarohin, Aliaksandr, Zhuang, Peiye, Xu, Yinghao, Yang, Ceyuan, Lin, Dahua, Zhou, Bolei, Tulyakov, Sergey, Lee, Hsin-Ying
We are witnessing significant breakthroughs in the technology for generating 3D objects from text. Existing approaches either leverage large text-to-image models to optimize a 3D representation or train 3D generators on object-centric datasets. Gener
Externí odkaz:
http://arxiv.org/abs/2312.08885
Recent approaches such as ControlNet offer users fine-grained spatial control over text-to-image (T2I) diffusion models. However, auxiliary modules have to be trained for each type of spatial condition, model architecture, and checkpoint, putting the
Externí odkaz:
http://arxiv.org/abs/2312.07536
Generating large-scale 3D scenes cannot simply apply existing 3D object synthesis technique since 3D scenes usually hold complex spatial configurations and consist of a number of objects at varying scales. We thus propose a practical and efficient 3D
Externí odkaz:
http://arxiv.org/abs/2312.02136