1 citations · 1 across the 10 of their papers we have counts for
10 papers
FreeFix: Boosting 3D Gaussian Splatting via Fine-Tuning-Free Diffusion Models
Hongyu Zhou, Zisen Shao, Sheng Miao +4
Neural Radiance Fields and 3D Gaussian Splatting have advanced novel view synthesis, yet still rely on dense inputs and often degrade at extrapolated views. Recent approaches lever…
EVolSplat4D: Efficient Volume-based Gaussian Splatting for 4D Urban Scene Synthesis
Sheng Miao, Sijin Li, Pan Wang +5
Novel view synthesis (NVS) of static and dynamic urban scenes is essential for autonomous driving simulation, yet existing methods often struggle to balance reconstruction time wit…
ScenDi: 3D-to-2D Scene Diffusion Cascades for Urban Generation
Hanlei Guo, Jiahao Shao, Xinya Chen +4
Recent advancements in 3D object generation using diffusion models have achieved remarkable success, but generating realistic 3D urban scenes remains challenging. Existing methods…
Spatial4D-Bench: A Versatile 4D Spatial Intelligence Benchmark
Pan Wang, Yang Liu, Guile Wu +23
4D spatial intelligence involves perceiving and processing how objects move or change over time. Humans naturally possess 4D spatial intelligence, supporting a broad spectrum of sp…
UnIRe: Unsupervised Instance Decomposition for Dynamic Urban Scene Reconstruction
Yunxuan Mao, Rong Xiong, Yue Wang +1
Reconstructing and decomposing dynamic urban scenes is crucial for autonomous driving, urban planning, and scene editing. However, existing methods fail to perform instance-aware d…
EVolSplat: Efficient Volume-based Gaussian Splatting for Urban View Synthesis
Sheng Miao, Jiaxin Huang, Dongfeng Bai +6
Novel view synthesis of urban scenes is essential for autonomous driving-related applications.Existing NeRF and 3DGS-based methods show promising results in achieving photorealisti…
Leverage Cross-Attention for End-to-End Open-Vocabulary Panoptic Reconstruction
Xuan Yu, Yuxuan Xie, Yili Liu +4
Open-vocabulary panoptic reconstruction offers comprehensive scene understanding, enabling advances in embodied robotics and photorealistic simulation. In this paper, we propose Pa…
UrbanCAD: Towards Highly Controllable and Photorealistic 3D Vehicles for Urban Scene Simulation
Yichong Lu, Yichi Cai, Shangzhan Zhang +5
Photorealistic 3D vehicle models with high controllability are essential for autonomous driving simulation and data augmentation. While handcrafted CAD models provide flexible cont…
-DBA: Neural Implicit Dense Bundle Adjustment Enables Image-Only Driving Scene Reconstruction
Yunxuan Mao, Bingqi Shen, Yifei Yang +4
The joint optimization of the sensor trajectory and 3D map is a crucial characteristic of bundle adjustment (BA), essential for autonomous driving. This paper presents -DBA, a n…
NGEL-SLAM: Neural Implicit Representation-based Global Consistent Low-Latency SLAM System
Yunxuan Mao, Xuan Yu, Kai Wang +3
Neural implicit representations have emerged as a promising solution for providing dense geometry in Simultaneous Localization and Mapping (SLAM). However, existing methods in this…