activity
20242026
most citedHUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting

2 citations · 3 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

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…

cs.CV2025★ 1 cited

Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation

Zhen Xu, Hongyu Zhou, Sida Peng +13

Depth estimation is a fundamental task in 3D computer vision, crucial for applications such as 3D reconstruction, free-viewpoint rendering, robotics, autonomous driving, and AR/VR…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Driving

Hongyu Zhou, Longzhong Lin, Jiabao Wang +6

In the past few decades, autonomous driving algorithms have made significant progress in perception, planning, and control. However, evaluating individual components does not fully…

cs.CV2024

PanopticRecon: Leverage Open-vocabulary Instance Segmentation for Zero-shot Panoptic Reconstruction

Xuan Yu, Yili Liu, Chenrui Han +5

Panoptic reconstruction is a challenging task in 3D scene understanding. However, most existing methods heavily rely on pre-trained semantic segmentation models and known 3D object…

cs.CV2024

-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…

cs.CV2024

Learning 3D-Aware GANs from Unposed Images with Template Feature Field

Xinya Chen, Hanlei Guo, Yanrui Bin +5

Collecting accurate camera poses of training images has been shown to well serve the learning of 3D-aware generative adversarial networks (GANs) yet can be quite expensive in pract…

cs.CV2024★ 2 cited

HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting

Hongyu Zhou, Jiahao Shao, Lu Xu +6

Holistic understanding of urban scenes based on RGB images is a challenging yet important problem. It encompasses understanding both the geometry and appearance to enable novel vie…