49 citations · 174 across the 38 of their papers we have counts for
32 papers · 1 filter
WorldExam: Benchmarking World Models from Apparent Appearance to Inherent Reactivity
Yuxue Yang, Shuyao Shang, Jiahe Wang +13
Controllable video generation models are increasingly being developed as world models. Accordingly, evaluating them in this role extends beyond the apparent appearance of generated…
PhiZero: A World Model Built Around Physical Language
Shuyao Shang, Yuqi Wang, Ruopeng Gao +4
We introduce PhiZero, a physical world model built around physical language, a compact discrete representation of world-state transitions. Existing physical world models typically…
ReinDriveGen: Reinforcement Post-Training for Out-of-Distribution Driving Scene Generation
Hao Zhang, Lue Fan, Weikang Bian +4
We present ReinDriveGen, a framework that enables full controllability over dynamic driving scenes, allowing users to freely edit actor trajectories to simulate safety-critical cor…
DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving
Shuyao Shang, Bing Zhan, Yunfei Yan +9
We propose DynVLA, a driving VLA model that introduces a new CoT paradigm termed Dynamics CoT. DynVLA forecasts compact world dynamics before action generation, enabling more infor…
GA-Drive: Geometry-Appearance Decoupled Modeling for Free-viewpoint Driving Scene Generation
Hao Zhang, Lue Fan, Qitai Wang +5
A free-viewpoint, editable, and high-fidelity driving simulator is crucial for training and evaluating end-to-end autonomous driving systems. In this paper, we present GA-Drive, a…
NeoVerse: Enhancing 4D World Model with in-the-wild Monocular Videos
Yuxue Yang, Lue Fan, Ziqi Shi +3
In this paper, we propose NeoVerse, a versatile 4D world model that is capable of 4D reconstruction, novel-trajectory video generation, and rich downstream applications. We first i…
MCOP: Multi-UAV Collaborative Occupancy Prediction
Zefu Lin, Wenbo Chen, Xiaojuan Jin +5
Unmanned Aerial Vehicle (UAV) swarm systems necessitate efficient collaborative perception mechanisms for diverse operational scenarios. Current Bird's Eye View (BEV)-based approac…
DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving
Yingyan Li, Shuyao Shang, Weisong Liu +10
Scaling Vision-Language-Action (VLA) models on large-scale data offers a promising path to achieving a more generalized driving intelligence. However, VLA models are limited by a `…
TC-Light: Temporally Coherent Generative Rendering for Realistic World Transfer
Yang Liu, Chuanchen Luo, Zimo Tang +6
Illumination and texture editing are critical dimensions for world-to-world transfer, which is valuable for applications including sim2real and real2real visual data scaling up for…
End-to-End Driving with Online Trajectory Evaluation via BEV World Model
Yingyan Li, Yuqi Wang, Yang Liu +3
End-to-end autonomous driving has achieved remarkable progress by integrating perception, prediction, and planning into a fully differentiable framework. Yet, to fully realize its…
FlexDrive: Toward Trajectory Flexibility in Driving Scene Reconstruction and Rendering
Jingqiu Zhou, Lue Fan, Linjiang Huang +4
Driving scene reconstruction and rendering have advanced significantly using the 3D Gaussian Splatting. However, most prior research has focused on the rendering quality along a pr…
LayerAnimate: Layer-level Control for Animation
Yuxue Yang, Lue Fan, Zuzeng Lin +2
Traditional animation production decomposes visual elements into discrete layers to enable independent processing for sketching, refining, coloring, and in-betweening. Existing ani…
GaussianPainter: Painting Point Cloud into 3D Gaussians with Normal Guidance
Jingqiu Zhou, Lue Fan, Xuesong Chen +3
In this paper, we present GaussianPainter, the first method to paint a point cloud into 3D Gaussians given a reference image. GaussianPainter introduces an innovative feed-forward…
FreeSim: Toward Free-viewpoint Camera Simulation in Driving Scenes
Lue Fan, Hao Zhang, Qitai Wang +2
We propose FreeSim, a camera simulation method for autonomous driving. FreeSim emphasizes high-quality rendering from viewpoints beyond the recorded ego trajectories. In such viewp…
OpenSatMap: A Fine-grained High-resolution Satellite Dataset for Large-scale Map Construction
Hongbo Zhao, Lue Fan, Yuntao Chen +6
In this paper, we propose OpenSatMap, a fine-grained, high-resolution satellite dataset for large-scale map construction. Map construction is one of the foundations of the transpor…
FreeVS: Generative View Synthesis on Free Driving Trajectory
Qitai Wang, Lue Fan, Yuqi Wang +2
Existing reconstruction-based novel view synthesis methods for driving scenes focus on synthesizing camera views along the recorded trajectory of the ego vehicle. Their image rende…
Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection
Guowen Zhang, Lue Fan, Chenhang He +3
Serialization-based methods, which serialize the 3D voxels and group them into multiple sequences before inputting to Transformers, have demonstrated their effectiveness in 3D obje…
Trim 3D Gaussian Splatting for Accurate Geometry Representation
Lue Fan, Yuxue Yang, Minxing Li +2
In this paper, we introduce Trim 3D Gaussian Splatting (TrimGS) to reconstruct accurate 3D geometry from images. Previous arts for geometry reconstruction from 3D Gaussians mainly…
Enhancing End-to-End Autonomous Driving with Latent World Model
Yingyan Li, Lue Fan, Jiawei He +4
In autonomous driving, end-to-end planners directly utilize raw sensor data, enabling them to extract richer scene features and reduce information loss compared to traditional plan…
CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians
Yang Liu, He Guan, Chuanchen Luo +4
The advancement of real-time 3D scene reconstruction and novel view synthesis has been significantly propelled by 3D Gaussian Splatting (3DGS). However, effectively training large-…
MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection
Yuxue Yang, Lue Fan, Zhaoxiang Zhang
Label-efficient LiDAR-based 3D object detection is currently dominated by weakly/semi-supervised methods. Instead of exclusively following one of them, we propose MixSup, a more pr…
SAGD: Boundary-Enhanced Segment Anything in 3D Gaussian via Gaussian Decomposition
Xu Hu, Yuxi Wang, Lue Fan +6
3D Gaussian Splatting has emerged as an alternative 3D representation for novel view synthesis, benefiting from its high-quality rendering results and real-time rendering speed. Ho…
Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving
Yuqi Wang, Jiawei He, Lue Fan +3
In autonomous driving, predicting future events in advance and evaluating the foreseeable risks empowers autonomous vehicles to better plan their actions, enhancing safety and effi…
FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxels
Lue Fan, Feng Wang, Naiyan Wang +1
LiDAR-based fully sparse architecture has garnered increasing attention. FSDv1 stands out as a representative work, achieving impressive efficacy and efficiency, albeit with intric…