activity
20232026
collaborators

9 papers

cs.CV2026

SPIRAL: Self-Evolving Action-Conditioned Video Generation via Reflective Planning Agents

Yu Yang, Yue Liao, Jianbiao Mei +11

Long-horizon action-conditioned video generation aims to synthesize temporally coherent videos that follow complex action instructions over extended horizons, requiring procedural…

cs.CV2025

Vision-Centric 4D Occupancy Forecasting and Planning via Implicit Residual World Models

Jianbiao Mei, Yu Yang, Xuemeng Yang +4

End-to-end autonomous driving systems increasingly rely on vision-centric world models to understand and predict their environment. However, a common ineffectiveness in these model…

cs.CV2025

X-Scene: Large-Scale Driving Scene Generation with High Fidelity and Flexible Controllability

Yu Yang, Alan Liang, Jianbiao Mei +3

Diffusion models are advancing autonomous driving by enabling realistic data synthesis, predictive end-to-end planning, and closed-loop simulation, with a primary focus on temporal…

cs.CL2025

O-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering

Jianbiao Mei, Tao Hu, Daocheng Fu +11

Large Language Models (LLMs), despite their advancements, are fundamentally limited by their static parametric knowledge, hindering performance on tasks requiring open-domain up-to…

cs.CV2024

DQFormer: Towards Unified LiDAR Panoptic Segmentation with Decoupled Queries

Yu Yang, Jianbiao Mei, Liang Liu +6

LiDAR panoptic segmentation, which jointly performs instance and semantic segmentation for things and stuff classes, plays a fundamental role in LiDAR perception tasks. While most…

cs.CV2024

Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving

Yu Yang, Jianbiao Mei, Yukai Ma +5

World models envision potential future states based on various ego actions. They embed extensive knowledge about the driving environment, facilitating safe and scalable autonomous…

cs.CV2023

Camera-based 3D Semantic Scene Completion with Sparse Guidance Network

Jianbiao Mei, Yu Yang, Mengmeng Wang +5

Semantic scene completion (SSC) aims to predict the semantic occupancy of each voxel in the entire 3D scene from limited observations, which is an emerging and critical task for au…

cs.CV2023

SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusion

Jianbiao Mei, Yu Yang, Mengmeng Wang +3

Semantic scene completion (SSC) jointly predicts the semantics and geometry of the entire 3D scene, which plays an essential role in 3D scene understanding for autonomous driving s…

cs.CV2023

PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation

Jianbiao Mei, Yu Yang, Mengmeng Wang +3

Reliable LiDAR panoptic segmentation (LPS), including both semantic and instance segmentation, is vital for many robotic applications, such as autonomous driving. This work propose…