3 citations · 8 across the 15 of their papers we have counts for
15 papers
DynFlowDrive: Flow-Based Dynamic World Modeling for Autonomous Driving
Xiaolu Liu, Yicong Li, Song Wang +3
Recently, world models have been incorporated into the autonomous driving systems to improve the planning reliability. Existing approaches typically predict future states through a…
VisionTrim: Unified Vision Token Compression for Training-Free MLLM Acceleration
Hanxun Yu, Wentong Li, Xuan Qu +3
Multimodal large language models (MLLMs) suffer from high computational costs due to excessive visual tokens, particularly in high-resolution and video-based scenarios. Existing to…
A Coarse-to-Fine Approach to Multi-Modality 3D Occupancy Grounding
Zhan Shi, Song Wang, Junbo Chen +1
Visual grounding aims to identify objects or regions in a scene based on natural language descriptions, essential for spatially aware perception in autonomous driving. However, exi…
PointLoRA: Low-Rank Adaptation with Token Selection for Point Cloud Learning
Song Wang, Xiaolu Liu, Lingdong Kong +6
Self-supervised representation learning for point cloud has demonstrated effectiveness in improving pre-trained model performance across diverse tasks. However, as pre-trained mode…
Uncertainty-Instructed Structure Injection for Generalizable HD Map Construction
Xiaolu Liu, Ruizi Yang, Song Wang +3
Reliable high-definition (HD) map construction is crucial for the driving safety of autonomous vehicles. Although recent studies demonstrate improved performance, their generalizat…
Inst3D-LMM: Instance-Aware 3D Scene Understanding with Multi-modal Instruction Tuning
Hanxun Yu, Wentong Li, Song Wang +2
Despite encouraging progress in 3D scene understanding, it remains challenging to develop an effective Large Multi-modal Model (LMM) that is capable of understanding and reasoning…
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…
PianoMotion10M: Dataset and Benchmark for Hand Motion Generation in Piano Performance
Qijun Gan, Song Wang, Shengtao Wu +1
Recently, artificial intelligence techniques for education have been received increasing attentions, while it still remains an open problem to design the effective music instrument…
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,…
Offboard Occupancy Refinement with Hybrid Propagation for Autonomous Driving
Hao Shi, Song Wang, Jiaming Zhang +5
Vision-based occupancy prediction, also known as 3D Semantic Scene Completion (SSC), presents a significant challenge in computer vision. Previous methods, confined to onboard proc…
Label-efficient Segmentation via Affinity Propagation
Wentong Li, Yuqian Yuan, Song Wang +5
Weakly-supervised segmentation with label-efficient sparse annotations has attracted increasing research attention to reduce the cost of laborious pixel-wise labeling process, whil…