9 citations · 14 across the 8 of their papers we have counts for
11 papers
PASTEL: Panoramic Alignment for Monocular 4D Scene Reconstruction
Yuankun Yang, Yi Wei, Bo Bai +2
Reconstructing 4D scenes from casually captured monocular video is vital for applications in virtual reality (VR) and embodied AI. Recent advances in 4D reconstruction and novel vi…
Unified Panoramic-Gaussian Representation for Monocular 4D Scene Synthesis
Yuankun Yang, Yi Wei, Wenyang Zhou +1
4D scene synthesis from monocular videos has made significant progress in recent years. However, existing methods are typically constrained by view interpolation. As a result, they…
DriveWeaver: Point-Conditioned Video Inpainting for Controllable Vehicle Insertion in Autonomous Driving Simulation
Junzhe Jiang, Zipei Ma, Zijie Pan +1
A pivotal step in autonomous driving simulation involves inserting foreground vehicles with predefined trajectories into simulated scenes. This process enhances scene diversity and…
DeMo++: Motion Decoupling for Autonomous Driving
Bozhou Zhang, Nan Song, Xiatian Zhu +1
Motion forecasting and planning are tasked with estimating the trajectories of traffic agents and the ego vehicle, respectively, to ensure the safety and efficiency of autonomous d…
4D Gaussian Splatting: Modeling Dynamic Scenes with Native 4D Primitives
Zeyu Yang, Zijie Pan, Xiatian Zhu +4
Dynamic 3D scene representation and novel view synthesis are crucial for enabling immersive experiences required by AR/VR and metaverse applications. It is a challenging task due t…
Reflective Gaussian Splatting
Yuxuan Yao, Zixuan Zeng, Chun Gu +2
Novel view synthesis has experienced significant advancements owing to increasingly capable NeRF- and 3DGS-based methods. However, reflective object reconstruction remains challeng…
Driving View Synthesis on Free-form Trajectories with Generative Prior
Zeyu Yang, Zijie Pan, Yuankun Yang +2
Driving view synthesis along free-form trajectories is essential for realistic driving simulations, enabling closed-loop evaluation of end-to-end driving policies. Existing methods…
Diffusion: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion Models
Zeyu Yang, Zijie Pan, Chun Gu +1
Recent advancements in 3D generation are predominantly propelled by improvements in 3D-aware image diffusion models. These models are pretrained on Internet-scale image data and fi…
Efficient4D: Fast Dynamic 3D Object Generation from a Single-view Video
Zijie Pan, Zeyu Yang, Xiatian Zhu +1
Generating dynamic 3D object from a single-view video is challenging due to the lack of 4D labeled data. An intuitive approach is to extend previous image-to-3D pipelines by transf…
WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation
Jiachen Lu, Ze Huang, Zeyu Yang +2
Generating multi-camera street-view videos is critical for augmenting autonomous driving datasets, addressing the urgent demand for extensive and varied data. Due to the limitation…
CBARF: Cascaded Bundle-Adjusting Neural Radiance Fields from Imperfect Camera Poses
Hongyu Fu, Xin Yu, Lincheng Li +1
Existing volumetric neural rendering techniques, such as Neural Radiance Fields (NeRF), face limitations in synthesizing high-quality novel views when the camera poses of input ima…