6 papers · 1 filter
Geospatial-Prior Guidance for 3D Semantic Scene Completion
Meng Wang, Shougao Zhang, Wenzhe He +4
Inferring complete 3D geometry and semantics from onboard images remains challenging because occlusions and restricted fields of view leave large scene regions underconstrained. Al…
Learning Temporal 3D Semantic Scene Completion via Optical Flow Guidance
Meng Wang, Fan Wu, Ruihui Li +3
3D Semantic Scene Completion (SSC) provides comprehensive scene geometry and semantics for autonomous driving perception, which is crucial for enabling accurate and reliable decisi…
Enhancing Small-Scale Dataset Expansion with Triplet-Connection-based Sample Re-Weighting
Ting Xiang, Changjian Chen, Zhuo Tang +5
The performance of computer vision models in certain real-world applications, such as medical diagnosis, is often limited by the scarcity of available images. Expanding datasets us…
Vision-based 3D Semantic Scene Completion via Capture Dynamic Representations
Meng Wang, Fan Wu, Yunchuan Qin +3
The vision-based semantic scene completion task aims to predict dense geometric and semantic 3D scene representations from 2D images. However, the presence of dynamic objects in th…
VLScene: Vision-Language Guidance Distillation for Camera-Based 3D Semantic Scene Completion
Meng Wang, Huilong Pi, Ruihui Li +3
Camera-based 3D semantic scene completion (SSC) provides dense geometric and semantic perception for autonomous driving. However, images provide limited information making the mode…
PAR: Prompt-Aware Token Reduction Method for Efficient Large Multimodal Models
Yingen Liu, Fan Wu, Ruihui Li +2
Multimodal large language models (MLLMs) demonstrate strong performance across visual tasks, but their efficiency is hindered by significant computational and memory demands from p…