5 papers
SGM-SLAM: Scene Graph Matching for Data-Efficient Distributed SLAM
Yewei Huang, Tixiao Shan, Abhinav Rajvanshi +4
We introduce a data-efficient distributed Simultaneous Localization and Mapping (SLAM) framework designed for a team of robots equipped with LiDAR, cameras, and inertial sensors. O…
Efficient Domain-Adaptive Multi-Task Dense Prediction with Vision Foundation Models
Beomseok Kang, Niluthpol Chowdhury Mithun, Mikhail Sizintsev +2
Multi-task dense prediction, which aims to jointly solve tasks like semantic segmentation and depth estimation, is crucial for robotics applications but suffers from domain shift w…
Graph2Nav: 3D Object-Relation Graph Generation to Robot Navigation
Tixiao Shan, Abhinav Rajvanshi, Niluthpol Mithun +1
We propose Graph2Nav, a real-time 3D object-relation graph generation framework, for autonomous navigation in the real world. Our framework fully generates and exploits both 3D obj…
DUDA: Distilled Unsupervised Domain Adaptation for Lightweight Semantic Segmentation
Beomseok Kang, Niluthpol Chowdhury Mithun, Abhinav Rajvanshi +2
Unsupervised Domain Adaptation (UDA) is essential for enabling semantic segmentation in new domains without requiring costly pixel-wise annotations. State-of-the-art (SOTA) UDA met…
Diffusion-Guided Gaussian Splatting for Large-Scale Unconstrained 3D Reconstruction and Novel View Synthesis
Niluthpol Chowdhury Mithun, Tuan Pham, Qiao Wang +6
Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. Howe…