Forging Spatial Intelligence

A Roadmap of Multi-Modal Data Pre-Training for Autonomous Systems

Figure 1: Taxonomy of Multi-Modal Representation Learning for Spatial Intelligence.

This repository serves as the official resource collection for the paper "Forging Spatial Intelligence: A Roadmap of Multi-Modal Data Pre-Training for Autonomous Systems".

In this work, we establish a systematic taxonomy for the field, unifying terminology, scope, and evaluation benchmarks. We organize existing methodologies into three complementary paradigms based on information flow and abstraction level:

• 📷 Single-Modality Pre-Training
  The Bedrock of Perception. Focuses on extracting foundational features from individual sensor streams (Camera or LiDAR) via self-supervised learning techniques, such as Contrastive Learning, Masked Modeling, and Forecasting. This paradigm establishes the fundamental representations for sensor-specific tasks.
• 🔄 Multi-Modality Pre-Training
  Bridging the Semantic-Geometric Gap. Leverages cross-modal synergy to fuse heterogeneous sensor data. This category includes LiDAR-Centric (distilling visual semantics into geometry), Camera-Centric (injecting geometric priors into vision), and Unified frameworks that jointly learn modality-agnostic representations.
• 🌍 Open-World Perception and Planning
  The Frontier of Embodied Autonomy. Represents the evolution from passive perception to active decision-making. This paradigm encompasses Generative World Models (e.g., video/occupancy generation), Embodied Vision-Language-Action (VLA) models, and systems capable of Open-World reasoning.

📄 Paper Link

Citation

If you find this work helpful for your research, please kindly consider citing our paper:

@article{wang2026forging,
    title   = {Forging Spatial Intelligence: A Roadmap of Multi-Modal Data Pre-Training for Autonomous Systems},
    author  = {Song Wang and Lingdong Kong and Xiaolu Liu and Hao Shi and Wentong Li and Jianke Zhu and Steven C. H. Hoi},
    journal = {arXiv preprint arXiv:2512.24385},
    year    = {2025}
}

Table of Contents

• 1. Benchmarks & Datasets
  • Vehicle-Based Datasets
  • Drone-Based Datasets
  • Other Datasets
• 2. Single-Modality Pre-Training
  • LiDAR-Only
  • Camera-Only
• 3. Multi-Modality Pre-Training
  • LiDAR-Centric (Vision-to-LiDAR)
  • Camera-Centric (LiDAR-to-Vision)
  • Unified Frameworks
• 4. Open-World Perception and Planning
  • Text-Grounded Understanding
  • Unified World Representation for Action
• 5. Acknowledgements

1. Benchmarks & Datasets

Vehicle-Based Datasets

Dataset	Venue	Sensor	Task	Website
KITTI	CVPR'12	2 Cam(RGB), 2 Cam(Gray), 1 LiDAR(64)	3D Det, Stereo, Optical Flow, SLAM
ApolloScape	TPAMI'19	2 Cam, 2 LiDAR	3D Det, HD Map
nuScenes	CVPR'20	6 Cam(RGB), 1 LiDAR(32), 5 Radar	3D Det, Seg, Occ, Map
SemanticKITTI	ICCV'19	4 Cam, 1 LiDAR(64)	3D Det, Occ
Waymo	CVPR'20	5 Cam(RGB), 5 LiDAR	Perception (Det, Seg, Track), Motion
Argoverse	CVPR'19	7 Cam(RGB), 2 LiDAR(32)	3D Tracking, Forecasting, Map
Lyft L5	CoRL'20	7 Cam(RGB), 3 LiDAR, 5 Radar	3D Det, Motion Forecasting/Planning
A*3D	ICRA'20	2 Cam, 1 LiDAR(64)	3D Det
KITTI-360	TPAMI'22	4 Cam, 1 LiDAR(64)	3D Det, Occ
A2D2	arXiv'20	6 Cam, 5 LiDAR(16)	3D Det
PandaSet	ITSC'21	6 Cam(RGB), 2 LiDAR(64)	3D Det, LiDAR Seg
Cirrus	ICRA'21	1 Cam, 2 LiDAR(64)	3D Det
ONCE	NeurIPS'21	7 Cam(RGB), 1 LiDAR(40)	3D Det (Self-supervised/Semi-supervised)
Shifts	arXiv'21	-	3D Det, HD Map
nuPlan	arXiv'21	8 Cam, 5 LiDAR	3D Det, HD Map, E2E Plan
Argoverse2	NeurIPS'21	7 Cam, 2 LiDAR(32)	3D Det, Occ, HD Map, E2E Plan
MONA	ITSC'22	3 Cam	3D Det, HD Map
Dual Radar	Sci. Data'25	1 Cam, 1 LiDAR(80) 2 Radar	3D Det
MAN TruckScenes	NeurIPS'24	4 Cam, 6 LiDAR(64), 6 RADAR	3D Det
OmniHD-Scenes	arXiv'24	6 Cam, 1 LiDAR(128), 6 RADAR	3D Det, Occ, HD Map
AevaScenes	2025	6 Cam, 6 LiDAR	3D Det, HD Map
PhysicalAI-AV	2025	7 Cam, 1 LiDAR, 11 RADAR	E2E Plan

Drone-Based Datasets

Dataset	Venue	Sensor	Task	Website
Campus	ECCV'16	1 Cam	Target Forecasting/ Tracking
UAV123	ECCV'16	1 Cam	UAV Trackong
CarFusion	CVPR'18	22 Cam	3D Vehicle Reconstruction
UAVDT	ECCV'18	1 Cam	2D Object Detection/ Tracking
DOTA	CVPR'18	Multi-Scoure	2D Object Detection
VisDrone	TPAMI'21	1 Cam	2D Object Detection/ Tracking
DOTA V2.0	TPAMI'21	Multi-Scoure	2D Object Detection
MOR-UAV	MM'20	1 Cam	Moving Object Recognation
AU-AIR	ICRA'20	1 Cam	2D Object Detection
UAVid	ISPRS JPRS'20	1 Cam	Semantic Segmentation
MOHR	Neuro'21	3 Cam	2D Object Detection
SensatUrban	CVPR'21	1 Cam	2D Object Detection
UAVDark135	TMC'22	1 Cam	2D Object Tracking
MAVREC	CVPR'24	1 Cam	2D Obejct Detection
BioDrone	IJCV'24	1 Cam	2D Object Tracking
PDT	ECCV'24	1 Cam, 1 LiDAR	2D Object Detection
UAV3D	NeurIPS'24	5 Cam	3D Object Detection/ Tracking
IndraEye	arXiv'24	1 Cam	2D Object Detection/ Semantic Segmentation
UAVScenes	ICCV'25	1 Cam, 1 LiDAR	Semantic Segmentation, Visual Localization

Other Robotic Platforms

Dataset	Venue	Platform	Sensors	Website
RailSem19	CVPRW'19	Railway	1× Camera
FRSign	arXiv'20	Railway	2× Camera (Stereo)
RAWPED	TVT'20	Railway	1× Camera
SRLC	AutCon'21	Railway	1× LiDAR
Rail-DB	MM'22	Railway	1× Camera
RailSet	IPAS'22	Railway	1× Camera
OSDaR23	ICRAE'23	Railway	9× Camera, 6× LiDAR, 1× Radar
Rail3D	Infra'24	Railway	4× Camera, 1× LiDAR
WHU-Railway3D	TITS'24	Railway	1× LiDAR
FloW	ICCV'21	USV (Water)	2× Camera, 1× 4D Radar
DartMouth	IROS'21	USV (Water)	3× Camera, 1× LiDAR
MODS	TITS'21	USV (Water)	2× Camera, 1× LiDAR
SeaSAW	CVPRW'22	USV (Water)	5× Camera
WaterScenes	T-ITS'24	USV (Water)	1× Camera, 1× 4D Radar
MVDD13	Appl. Ocean Res.'24	USV (Water)	1× Camera
SeePerSea	TFR'25	USV (Water)	1× Camera, 1× LiDAR
WaterVG	TITS'25	USV (Water)	1× Camera, 1× 4D Radar
Han et al.	NMI'24	Legged Robot	1× Depth Camera
Luo et al.	CVPR'25	Legged Robot	1× Panoramic Camera
QuadOcc	arXiv'25	Legged Robot	1× Panoramic Camera, 1× LiDAR
M3ED	CVPRW'23	Multi-Robot	3× Camera, 2× Event Camera, 1× LiDAR
Pi3DET	ICCV'25	Multi-Robot	3× Camera, 2× Event Camera, 1× LiDAR

2. Single-Modality Pre-Training

LiDAR-Only

Methods utilizing Point Cloud Contrastive Learning, Masked Autoencoders (MAE), or Forecasting.

Model	Paper	Venue	GitHub
PointContrast	Unsupervised Pre-training for 3D Point Cloud Understanding	ECCV 2020
DepthContrast	Self-supervised Pretraining of 3D Features on any Point-Cloud	ICCV 2021
GCC-3D	Exploring geometry-aware contrast and clustering harmonization for self-supervised 3d object detection	ICCV 2021
ContrastiveSceneContexts	Exploring data-efficient 3d scene understanding with contrastive scene contexts	CVPR 2021
SegContrast	3D Point Cloud Feature Representation Learning through Self-supervised Segment Discrimination	RA-L 2021
GroupContrast	Groupcontrast: Semantic-aware self-supervised representation learning for 3d understanding	CVPR 2024
ProposalContrast	Unsupervised Pre-training for LiDAR-Based 3D Object Detection	ECCV 2022
Occupancy-MAE	Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders	T-IV 2023
ALSO	Automotive LiDAR Self-supervision by Occupancy Estimation	CVPR 2023
GD-MAE	Generative Decoder for MAE Pre-training on LiDAR Point Clouds	CVPR 2023
AD-PT	Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset	NeurIPS 2023
E-SSL	Equivariant spatio-temporal self-supervision for lidar object detection	ECCV 2024
PatchContrast	Self-Supervised Pre-training for 3D Object Detection	CVPRW 2025
MV-JAR	Mv-jar: Masked voxel jigsaw and reconstruction for lidar-based self-supervised pre-training	CVOR 2023
Occupancy-MAE	Occupancy-mae: Self-supervised pre-training large-scale lidar point clouds with masked occupancy autoencoders	TIV 2023
Core	Core: Cooperative reconstruction for multi-agent perception	ICCV 2023
MAELi	Masked Autoencoder for Large-Scale LiDAR Point Clouds	WACV 2024
BEV-MAE	Bird's Eye View Masked Autoencoders for Point Cloud Pre-training	AAAI 2024
AD-L-JEPA	AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR Data	AAAI 2026
UnO	Unsupervised Occupancy Fields for Perception and Forecasting	CVPR 2024
BEVContrast	Self-Supervision in BEV Space for Automotive Lidar Point Clouds	3DV 2024
4DContrast	4dcontrast: Contrastive learning with dynamic correspondences for 3d scene understanding	ECCV 2022
Copilot4D	Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion	ICLR 2024
T-MAE	Temporal Masked Autoencoders for Point Cloud Representation Learning	ECCV 2024
PICTURE	Point Cloud Reconstruction Is Insufficient to Learn 3D Representations	ACM MM 2024
LSV-MAE	Rethinking Masked-Autoencoder-Based 3D Point Cloud Pretraining	IV 2024
UNIT	Unsupervised Online Instance Segmentation through Time	arXiv 2024
R-MAE	Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders	arXiv 2024
TurboTrain	TurboTrain: Towards efficient and balanced multi-task learning for multi-agent perception and prediction	ICCV 2025
NOMAE	Multi-Scale Neighborhood Occupancy Masked Autoencoder for Self-Supervised Learning in LiDAR Point Clouds	CVPR 2025
4D Occ	Point cloud forecasting as a proxy for 4d occupancy forecasting	CVPR 2023
GPICTURE	Mutual information-driven self-supervised point cloud pre-training	KBS 2025
CooPre	CooPre: Cooperative pretraining for v2x cooperative perception	IROS 2025
TREND	TREND: Unsupervised 3D Representation Learning via Temporal Forecasting for LiDAR Perception	arXiv 2024

Camera-Only

Self-supervised learning from image sequences for driving/robotics.

Model	Paper	Venue	GitHub
INoD	Injected Noise Discriminator for Self-Supervised Representation	RA-L 2023
TempO	Self-Supervised Representation Learning From Temporal Ordering	RA-L 2024
LetsMap	Unsupervised Representation Learning for Label-Efficient Semantic BEV Mapping	ECCV 2024
NeRF-MAE	Masked AutoEncoders for Self-Supervised 3D Representation Learning	ECCV 2024
VisionPAD	A Vision-Centric Pre-training Paradigm for Autonomous Driving	arXiv 2024

3. Multi-Modality Pre-Training

LiDAR-Centric Pre-Training

Enhancing LiDAR representations using Vision foundation models (Knowledge Distillation).

Model	Paper	Venue	GitHub
SLidR	Image-to-Lidar Self-Supervised Distillation	CVPR 2022
SimIPU	Simipu: Simple 2d image and 3d point cloud unsupervised pre-training for spatial-aware visual representations	AAAI 2022
SSPC-Im	Self-supervised pre-training of 3d point cloud networks with image data	CoRL 2022
ST-SLidR	Self-Supervised Image-to-Point Distillation via Semantically Tolerant Contrastive Loss	CVPR 2023
I2P-MAE	Learning 3D Representations from 2D Pre-trained Models via Image-to-Point MAE	CVPR 2023
TriCC	Unsupervised 3D Point Cloud Representation Learning by Triangle Constrained Contrast	CVPR 2023
Seal	Segment Any Point Cloud Sequences by Distilling Vision FMs	NeurIPS 23
PRED	Pre-training via Semantic Rendering on LiDAR Point Clouds	NeurIPS 23
LiMA	Beyond one shot, beyond one perspective: Cross-view and long-horizon distillation for better lidar representations	ICCV 2025
ImageTo360	360° from a Single Camera: A Few-Shot Approach for LiDAR Segmentation	ICCVW 2023
ScaLR	Three Pillars improving Vision Foundation Model Distillation for Lidar	CVPR 2024
CSC	Building a Strong Pre-Training Baseline for Universal 3D Large-Scale Perception	CVPR 2024
GPC	Pre-Training LiDAR-Based 3D Object Detectors Through Colorization	ICLR 2024
Cross-Modal SSL	Cross-Modal Self-Supervised Learning with Effective Contrastive Units	IROS 2024
SuperFlow	4D Contrastive Superflows are Dense 3D Representation Learners	ECCV 2024
Rel	Image-to-Lidar Relational Distillation for Autonomous Driving Data	ECCV 2024
HVDistill	Transferring Knowledge from Images to Point Clouds via Unsupervised Hybrid-View Distillation	IJCV 2024
RadarContrast	Self-Supervised Contrastive Learning for Camera-to-Radar Knowledge Distillation	DCOSS-IoT 2024
CM3D	Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection	CoRL 2024
OLIVINE	Fine-grained Image-to-LiDAR Contrastive Distillation with Visual Foundation Models	NeurIPS 2024
EUCA-3DP	Exploring the Untouched Sweeps for Conflict-Aware 3D Segmentation Pretraining	arXiv 2024
GASP	Gasp: Unifying geometric and semantic self-supervised pre-training for autonomous driving	arXiv 2025
BALViT	Label-Efficient LiDAR Scene Understanding with 2D-3D Vision Transformer Adapters	ICRAW 2025

Camera-Centric Pre-Training

Learning 3D Geometry from Camera inputs using LiDAR supervision.

Model	Paper	Venue	GitHub
DD3D	Is Pseudo-Lidar needed for Monocular 3D Object detection?	ICCV 2021
DEPT	Delving into the Pre-training Paradigm of Monocular 3D Object Detection	arXiv 2022
OccNet	Scene as Occupancy	ICCV 2023
GeoMIM	Towards Better 3D Knowledge Transfer via Masked Image Modeling	ICCV 2023
GAPretrain	Geometric-aware Pretraining for Vision-centric 3D Object Detection	arXiv 2023
UniScene	Multi-Camera Unified Pre-training via 3D Scene Reconstruction	RA-L 2024
SelfOcc	Self-Supervised Vision-Based 3D Occupancy Prediction	CVPR 2024
ViDAR	Visual Point Cloud Forecasting enables Scalable Autonomous Driving	CVPR 2024
DriveWorld	4D Pre-trained Scene Understanding via World Models	CVPR 2024
OccFeat	Self-supervised Occupancy Feature Prediction for Pretraining BEV Segmentation	CVPRW 2024
OccWorld	Learning a 3D Occupancy World Model for Autonomous Driving	ECCV 2024
MVS3D	Exploiting the Potential of Multi-Frame Stereo Depth Estimation Pre-training	IJCNN 2024
OccSora	4D Occupancy Generation Models as World Simulators	arXiv 2024
MIM4D	Masked Modeling with Multi-View Video for Autonomous Driving	arXiv 2024
GaussianPretrain	A Simple Unified 3D Gaussian Representation for Visual Pre-training	arXiv 2024
S3PT	S3pt: Scene semantics and structure guided clustering to boost self-supervised pre-training for autonomous driving	WACV 2025
UniFuture	Seeing the Future, Perceiving the Future: A Unified Driving World Model for Future Generation and Perception	arXiv 2025
GaussianOcc	Gaussianocc: Fully self-supervised and efficient 3d occupancy estimation with gaussian splatting	ICCV 2025
GaussianTR	Gausstr: Foundation model-aligned gaussian transformer for self-supervised 3d spatial understanding	CVPR 2025
DistillNeRF	Distillnerf: Perceiving 3d scenes from single-glance images by distilling neural fields and foundation model features	NeurIPS 2024

Unified Pre-Training

Joint optimization of multi-modal encoders for unified representations.

Model	Paper	Venue	GitHub
PonderV2	Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm	arXiv 2023
UniPAD	A Universal Pre-training Paradigm for Autonomous Driving	CVPR 2024
UniM2AE	Multi-Modal Masked Autoencoders with Unified 3D Representation	ECCV 2024
ConDense	Consistent 2D/3D Pre-training for Dense and Sparse Features	ECCV 2024
Unified Pretrain	Learning Shared RGB-D Fields: Unified Self-supervised Pre-training	arXiv 2024
BEVWorld	A Multimodal World Simulator for Autonomous Driving via Unified BEV Latent Space	arXiv 2024
NS-MAE	Learning Shared RGB-D Fields: Unified Self-supervised Pre-training for Label-efficient LiDAR-Camera 3D Perception	arXiv 2024
CLAP	CLAP: Unsupervised 3D Representation Learning for Fusion 3D Perception via Curvature Sampling and Prototype Learning	arXiv 2024
GS3	Point Cloud Unsupervised Pre-training via 3D Gaussian Splatting	arXiv 2024
Hermes	Hermes: A unified self-driving world model for simultaneous 3d scene understanding and generation	ICCV 2025
LRS4Fusion	Self-Supervised Sparse Sensor Fusion for Long Range Perception	ICCV 2025
Gaussian2Scene	Gaussian2Scene: 3D Scene Representation Learning via Self-supervised Learning with 3D Gaussian Splatting	arXiv 2025

Incorporating Additional Sensors: With Radar

Incorporating additional modalities into pre-training frameworks for representation learning.

Model	Paper	Venue	GitHub
RadarContrast	Self-Supervised Contrastive Learning for Camera-to-Radar Knowledge Distillation	DCOSS-IoT 2024
AssociationNet	Radar camera fusion via representation learning in autonomous driving	CVPRW 2021
MVRAE	Multi-View Radar Autoencoder for Self-Supervised Automotive Radar Representation Learning	IV 2024
SSRLD	Self-supervised representation learning for the object detection of marine radar	ICCAI 2022
U-MLPNet	Learning Omni-Dimensional Spatio-Temporal Dependencies for Millimeter-Wave Radar Perception	Remote Sens 2024
4D-ROLLS	4D-ROLLS: 4D Radar Occupancy Learning via LiDAR Supervision	arXiv 2025
SS-RODNet	Pre-Training For mmWave Radar Object Detection Through Masked Image Modeling	SS-RODNet
Radical	Bootstrapping autonomous driving radars with self-supervised learning	CVPR 2024
RiCL	Leveraging Self-Supervised Instance Contrastive Learning for Radar Object Detection	arXiv 2024
RSLM	Radar spectra-language model for automotive scene parsing	RADAR 2024

Incorporating Additional Sensors: With Event Camera

Model	Paper	Venue	GitHub
ECDP	Event Camera Data Pre-training	ICCV 2023
MEM	Masked Event Modeling: Self-Supervised Pretraining for Event Cameras	WACV 2024
DMM	Data-efficient event camera pre-training via disentangled masked modeling	arXiv 2024
STP	Enhancing Event Camera Data Pretraining via Prompt-Tuning with Visual Models	-
ECDDP	Event Camera Data Dense Pre-training	ECCV2024
EventBind	Eventbind: Learning a unified representation to bind them all for event-based open-world understanding	ECCV2024
EventFly	EventFly: Event Camera Perception from Ground to the Sky	CVPR 2025

4. Open-World Perception and Planning

Text-Grounded Understanding

Model	Paper	Venue	GitHub
CLIP2Scene	Towards Label-efficient 3D Scene Understanding by CLIP	CVPR 2023
OpenScene	3D Scene Understanding with Open Vocabularies	CVPR 2023
CLIP-ZSPCS	Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation	MM 2023
CLIP-FO3D	Learning Free Open-world 3D Scene Representations from 2D Dense CLIP	ICCVW 2023
POP-3D	Open-Vocabulary 3D Occupancy Prediction from Images	NeurIPS 2023
VLM2Scene	Self-Supervised Image-Text-LiDAR Learning with Foundation Models	AAAI 2024
IntraCorr3D	Hierarchical intra-modal correlation learning for label-free 3d semantic segmentation	CVPR 2024
SAL	Better Call SAL: Towards Learning to Segment Anything in Lidar	ECCV 2024
Affinity3D	Propagating Instance-Level Semantic Affinity for Zero-Shot Semantic Seg	ACM MM 2024
UOV	3D Unsupervised Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving	arXiv 2024
OVO	OVO: Open-Vocabulary Occupancy	arXiv 2023
LangOcc	Langocc: Self-supervised open vocabulary occupancy estimation via volume rendering	3DV 2025
VEON	VEON: Vocabulary-Enhanced Occupancy Prediction	ECCV 2024
LOcc	Language Driven Occupancy Prediction	ICCV 2025
UP-VL	Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving	ICCV 2023
ZPCS-MM	See more and know more: Zero-shot point cloud segmentation via multi-modal visual data	ICCV 2023
CNS	Towards label-free scene understanding by vision foundation models	NeurIPS
3DOV-VLD	3D Open-Vocabulary Panoptic Segmentation with 2D-3D Vision-Language Distillation	ECCV 2024
CLIP^2	CLIP2: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data	CVPR 2023
AdaCo	Adaco: Overcoming visual foundation model noise in 3d semantic segmentation via adaptive label correction	AAAI 2025
TT-Occ	TT-Occ: Test-Time Compute for Self-Supervised Occupancy via Spatio-Temporal Gaussian Splatting	arXiv 2025
AutoOcc	AutoOcc: Automatic Open-Ended Semantic Occupancy Annotation via Vision-Language Guided Gaussian Splatting	ICCV 2025

Unified World Representation for Action

Model	Paper	Venue	GitHub
OccWorld	OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving	ECCV 2024
GenAD	Generalized Predictive Model for Autonomous Driving	CVPR 2024
OccSora	OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving	arXiv 2024
OccLLaMA	OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving	arXiv 2024
OccVAR	OccVAR: Scalable 4D Occupancy Prediction via Next-Scale Prediction	-
RenderWorld	Renderworld: World Model with Self-Supervised 3D Label	ICRA 2025
Drive-OccWorld	Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving	AAAI 2025
LAW	Enhancing End-to-End Autonomous Driving with Latent World Model	ICLR 2025
FSF-Net	FSF-Net: Enhance 4D occupancy forecasting with coarse BEV scene flow for autonomous driving	PR 2025
DriveX	DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving	arXiv 2025
SPOT	SPOT: Scalable 3D Pre-training via Occupancy Prediction for Autonomous Driving	TPAMI 2025
WoTE	End-to-End Driving with Online Trajectory Evaluation via BEV World Model	ICCV 2025
FASTopoWM	FASTopoWM: Fast-Slow Lane Segment Topology Reasoning with Latent World Models	arXiv 2025
OccTens	OccTENS: 3D Occupancy World Model via Temporal Next-Scale Prediction	arXiv 2025
OccVLA	Occvla: Vision-language-action model with implicit 3d occupancy supervision	arXIv 2025
World4Drive	World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model	ICCV 2025

5. Acknowledgements

We thank the authors of the referenced papers for their open-source contributions.