1 citations · 2 across the 8 of their papers we have counts for
10 papers
SparseOcc++: Geometry-Aware Sparse Latent Representation for Semantic Occupancy Prediction
Pin Tang, Zhongdao Wang, Guoqing Wang +2
Vision-based 3D semantic occupancy prediction is essential for autonomous driving, yet dense voxel representations waste computation on largely empty space, while BEV and TPV proje…
Targeted Structure Completion for Sparse-View 3D Reconstruction in Autonomous Driving
Guoqing Wang, Pin Tang, Xiangxuan Ren +2
Reconstructing 3D scene structures from sparse, low-overlap observations remains a fundamental challenge in autonomous driving. Recent state-of-the-art frameworks achieve promising…
PixelPilot: Scalable Vision-Language-Action Models for End-to-End Autonomous Driving
Pin Tang, Guoqing Wang, Xiangxuan Ren +4
Vision-Language-Action Models (VLAs), which leverage the advanced reasoning capabilities of Vision-Language Models (VLMs), show promising generalization in complex autonomous drivi…
Learning Vision-Language-Action World Models for Autonomous Driving
Guoqing Wang, Pin Tang, Xiangxuan Ren +3
Vision-Language-Action (VLA) models have recently achieved notable progress in end-to-end autonomous driving by integrating perception, reasoning, and control within a unified mult…
LiteFusion: Taming 3D Object Detectors from Vision-Based to Multi-Modal with Minimal Adaptation
Xiangxuan Ren, Zhongdao Wang, Pin Tang +3
3D object detection is fundamental for safe and robust intelligent transportation systems. Current multi-modal 3D object detectors often rely on complex architectures and training…
Grounding Everything in Tokens for Multimodal Large Language Models
Xiangxuan Ren, Zhongdao Wang, Liping Hou +3
Multimodal large language models (MLLMs) have made significant advancements in vision understanding and reasoning. However, the autoregressive Transformer architecture used by MLLM…
VEON: Vocabulary-Enhanced Occupancy Prediction
Jilai Zheng, Pin Tang, Zhongdao Wang +4
Perceiving the world as 3D occupancy supports embodied agents to avoid collision with any types of obstacle. While open-vocabulary image understanding has prospered recently, how t…
OccGen: Generative Multi-modal 3D Occupancy Prediction for Autonomous Driving
Guoqing Wang, Zhongdao Wang, Pin Tang +4
Existing solutions for 3D semantic occupancy prediction typically treat the task as a one-shot 3D voxel-wise segmentation perception problem. These discriminative methods focus on…
SparseOcc: Rethinking Sparse Latent Representation for Vision-Based Semantic Occupancy Prediction
Pin Tang, Zhongdao Wang, Guoqing Wang +4
Vision-based perception for autonomous driving requires an explicit modeling of a 3D space, where 2D latent representations are mapped and subsequent 3D operators are applied. Howe…
Single-Model and Any-Modality for Video Object Tracking
Zongwei Wu, Jilai Zheng, Xiangxuan Ren +5
In the realm of video object tracking, auxiliary modalities such as depth, thermal, or event data have emerged as valuable assets to complement the RGB trackers. In practice, most…