8 papers · 1 filter
Bridging 3D Gaussians and Semantic Occupancy for Comprehensive Open-Vocabulary Scene Understanding from Unposed Images
Hu Zhu, Bohan Li, Xianda Guo +5
Comprehensive 3D scene understanding from sparse, unposed images requires a model to recover renderable geometry, open-vocabulary semantics, and free/occupied 3D space without rely…
Interpretable Single-View 3D Gaussian Splatting using Unsupervised Hierarchical Disentangled Representation Learning
Yuyang Zhang, Baao Xie, Hu Zhu +4
Gaussian Splatting (GS) has recently marked a significant advancement in 3D reconstruction, delivering both rapid rendering and high-quality results. However, existing 3DGS methods…
OccScene: Semantic Occupancy-based Cross-task Mutual Learning for 3D Scene Generation
Bohan Li, Xin Jin, Jianan Wang +8
Recent diffusion models have demonstrated remarkable performance in both 3D scene generation and perception tasks. Nevertheless, existing methods typically separate these two proce…
Hierarchical Context Alignment with Disentangled Geometric and Temporal Modeling for Semantic Occupancy Prediction
Bohan Li, Jiajun Deng, Yasheng Sun +3
Camera-based 3D Semantic Occupancy Prediction (SOP) is crucial for understanding complex 3D scenes from limited 2D image observations. Existing SOP methods typically aggregate cont…
UniScene: Unified Occupancy-centric Driving Scene Generation
Bohan Li, Jiazhe Guo, Hongsi Liu +14
Generating high-fidelity, controllable, and annotated training data is critical for autonomous driving. Existing methods typically generate a single data form directly from a coars…
Hierarchical Temporal Context Learning for Camera-based Semantic Scene Completion
Bohan Li, Jiajun Deng, Wenyao Zhang +4
Camera-based 3D semantic scene completion (SSC) is pivotal for predicting complicated 3D layouts with limited 2D image observations. The existing mainstream solutions generally lev…