9 papers · 1 filter
A Unified Framework for Image-to-3D Part Generation via Variable Granularity
Qiwen Gu, Xin Zhou, Xiwu Chen +3
Controllable 3D part generation is pivotal for digital asset creation, yet existing methods lack the flexibility to accommodate diverse user workflows requiring varying levels of c…
GeoUniPR: A Geometry-Consistent Unified Framework for Cross-Modal Place Recognition
Wonbong Kim, Jiatong Xiao, Rui Li +5
Cross-modal place recognition (CMPR) aims to identify the same location across heterogeneous sensing modalities, such as vision and LiDAR. Existing methods commonly bridge the moda…
From Open Waters to Enclosed Cabins: ProteusVPR for Cross-Scene Visual Place Recognition in Maritime Perception and Cabin Inspection
Zexi Chen, Zitai Huang, Qiwen Gu +6
Autonomous robotic inspection in maritime environments presents unique challenges for Visual Place Recognition (VPR) due to cross-scene perceptual shifts. Robots navigating ship-bo…
Signal Structure-Aware Gaussian Splatting for Large-Scale Scene Reconstruction
Weiyi Xue, Fan Lu, Chi Zhang +6
3D Gaussian Splatting has demonstrated remarkable potential in novel view synthesis. In contrast to small-scale scenes, large-scale scenes inevitably contain sparsely observed regi…
MU-GeNeRF: Multi-view Uncertainty-guided Generalizable Neural Radiance Fields for Distractor-aware Scene
Wenjie Mu, Zhan Li, Chuanzhou Su +8
Generalizable Neural Radiance Fields (GeNeRFs) enable high-quality scene reconstruction from sparse views and can generalize to unseen scenes. However, in real-world settings, tran…
Learning from Mistakes: Loss-Aware Memory Enhanced Continual Learning for LiDAR Place Recognition
Xufei Wang, Junqiao Zhao, Siyue Tao +3
LiDAR place recognition plays a crucial role in SLAM, robot navigation, and autonomous driving. However, existing LiDAR place recognition methods often struggle to adapt to new env…
LDRFusion: A LiDAR-Dominant multimodal refinement framework for 3D object detection
Jijun Wang, Yan Wu, Yujian Mo +3
Existing LiDAR-Camera fusion methods have achieved strong results in 3D object detection. To address the sparsity of point clouds, previous approaches typically construct spatial p…
Enhancing LiDAR Point Features with Foundation Model Priors for 3D Object Detection
Yujian Mo, Yan Wu, Junqiao Zhao +3
Recent advances in foundation models have opened up new possibilities for enhancing 3D perception. In particular, DepthAnything offers dense and reliable geometric priors from mono…
Ranking-aware Continual Learning for LiDAR Place Recognition
Xufei Wang, Gengxuan Tian, Junqiao Zhao +4
Place recognition plays a significant role in SLAM, robot navigation, and autonomous driving applications. Benefiting from deep learning, the performance of LiDAR place recognition…