3 citations · 8 across the 15 of their papers we have counts for
7 papers · 2 filters
ReliOcc: Towards Reliable Semantic Occupancy Prediction via Uncertainty Learning
Song Wang, Zhongdao Wang, Jiawei Yu +4
Vision-centric semantic occupancy prediction plays a crucial role in autonomous driving, which requires accurate and reliable predictions from low-cost sensors. Although having not…
TokenPacker: Efficient Visual Projector for Multimodal LLM
Wentong Li, Yuqian Yuan, Jian Liu +5
The visual projector serves as an essential bridge between the visual encoder and the Large Language Model (LLM) in a Multimodal LLM (MLLM). Typically, MLLMs adopt a simple MLP to…
Label-efficient Semantic Scene Completion with Scribble Annotations
Song Wang, Jiawei Yu, Wentong Li +4
Semantic scene completion aims to infer the 3D geometric structures with semantic classes from camera or LiDAR, which provide essential occupancy information in autonomous driving.…
DTCLMapper: Dual Temporal Consistent Learning for Vectorized HD Map Construction
Siyu Li, Jiacheng Lin, Hao Shi +5
Temporal information plays a pivotal role in Bird's-Eye-View (BEV) driving scene understanding, which can alleviate the visual information sparsity. However, the indiscriminate tem…
Not All Voxels Are Equal: Hardness-Aware Semantic Scene Completion with Self-Distillation
Song Wang, Jiawei Yu, Wentong Li +4
Semantic scene completion, also known as semantic occupancy prediction, can provide dense geometric and semantic information for autonomous vehicles, which attracts the increasing…
MGMap: Mask-Guided Learning for Online Vectorized HD Map Construction
Xiaolu Liu, Song Wang, Wentong Li +3
Currently, high-definition (HD) map construction leans towards a lightweight online generation tendency, which aims to preserve timely and reliable road scene information. However,…