11 papers
ProSGNeRF: Progressive Dynamic Neural Scene Graph with Frequency Modulated Foundation Model in Urban Scenes
Tianchen Deng, Yanbo Wang, Yejia Liu +5
Implicit neural representation has demonstrated promising results in 3D reconstruction on various scenes. However, existing approaches either struggle to model fast-moving objects…
Graph-Loc: Robust Graph-Based LiDAR Pose Tracking with Compact Structural Map Priors under Low Observability and Occlusion
Wentao Zhao, Yihe Niu, Zikun Chen +4
Map-based LiDAR pose tracking is essential for long-term autonomous operation, where onboard map priors need be compact for scalable storage and fast retrieval, while online observ…
ViT-Up: Faithful Feature Upsampling for Vision Transformers
Krispin Wandel, Jingchuan Wang, Hesheng Wang
Vision Transformers (ViTs) have become a dominant architecture for visual representation learning, providing exceptionally strong and broadly reusable backbone features. However, V…
OTPL-VIO: Robust Visual-Inertial Odometry with Optimal Transport Line Association and Adaptive Uncertainty
Zikun Chen, Wentao Zhao, Yihe Niu +2
Robust stereo visual-inertial odometry (VIO) remains challenging in low-texture scenes and under abrupt illumination changes, where point features become sparse and unstable, leadi…
What Is The Best 3D Scene Representation for Robotics? From Geometric to Foundation Models
Tianchen Deng, Yue Pan, Shenghai Yuan +10
In this paper, we provide a comprehensive overview of existing scene representation methods for robotics, covering traditional representations such as point clouds, voxels, signed…
Guided Diffusion-based Generation of Adversarial Objects for Real-World Monocular Depth Estimation Attacks
Yongtao Chen, Yanbo Wang, Wentao Zhao +3
Monocular Depth Estimation (MDE) serves as a core perception module in autonomous driving systems, but it remains highly susceptible to adversarial attacks. Errors in depth estimat…