mlsanityData to 7 Oct 2026

LangDriveCTRL: Natural Language Controllable Driving Scene Editing with Multi-modal Agents

arXiv 2512.17445 ↗First posted 19 Dec 2025cs.CVcited by 3

Not on the map. Why?

Abstract (arXiv)

LangDriveCTRL is a natural-language-controllable framework for editing real-world driving videos to synthesize diverse traffic scenarios. It represents each video as an explicit 3D scene graph, decomposing the scene into a static background and dynamic object nodes. To enable fine-grained editing and realism, it introduces a feedback-driven agentic pipeline. An Orchestrator converts user instructions into executable graphs that coordinate specialized multi-modal agents and tools. An Object Grounding Agent aligns free-form text with target object nodes in the scene graph; a Behavior Editing Agent generates multi-object trajectories from language instructions; and a Behavior Reviewer Agent iteratively reviews and refines the generated trajectories. The edited scene graph is rendered and harmonized using a video diffusion tool, and then further refined by a Video Reviewer Agent to ensure photorealism and appearance alignment. LangDriveCTRL supports both object node editing (removal, insertion, and replacement) and multi-object behavior editing from natural-language instructions. Quantitatively, it achieves nearly 2× higher instruction alignment than the previous SoTA, with superior photorealism, structural preservation, and traffic realism. Project page is available at: https://yunhe24.github.io/langdrivectrl/.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 52 of its 60 references that are in the map. First posted on arXiv 19 Dec 2025.

Builds on

52 of 60 references.

References · 52

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2023GPT-4 Technical Reportcited by 18,132
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  5. 2020Denoising Diffusion Implicit Modelscited by 9,655
  6. 2023Segment Anythingcited by 8,158
  7. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,893
  8. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  9. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  10. 2024GPT-4o System Cardcited by 4,467
  11. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  12. 2023Qwen Technical Reportcited by 3,273
38 more
  1. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,436
  2. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  3. 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,198
  4. 2018Towards Accurate Generative Models of Video: A New Metric & Challengescited by 1,204
  5. 20234D Gaussian Splatting for Real-Time Dynamic Scene Renderingcited by 1,144
  6. 2024Grounded SAM: Assembling Open-World Models for Diverse Visual Taskscited by 914
  7. 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 720
  8. 2017AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehiclescited by 517
  9. 2023LangSplat: 3D Language Gaussian Splattingcited by 410
  10. 2025Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generationcited by 342
  11. 2023Track Anything: Segment Anything Meets Videoscited by 230
  12. 2023Language Embedded 3D Gaussians for Open-Vocabulary Scene Understandingcited by 205
  13. 2023Segment and Track Anythingcited by 193
  14. 2024DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generationcited by 186
  15. 2025World Simulation with Video Foundation Models for Physical AIcited by 183
  16. 2025Difix3D+: Improving 3D Reconstructions with Single-Step Diffusion Modelscited by 160
  17. 2024OmniRe: Omni Urban Scene Reconstructioncited by 159
  18. 2023Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusioncited by 137
  19. 2024SceneCraft: An LLM Agent for Synthesizing 3D Scene as Blender Codecited by 125
  20. 2025TrajectoryCrafter: Redirecting Camera Trajectory for Monocular Videos via Diffusion Modelscited by 120
  21. 2024Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agentscited by 91
  22. 2024GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Controlcited by 76
  23. 2025WOD-E2E: Waymo Open Dataset for End-to-End Driving in Challenging Long-tail Scenarioscited by 60
  24. 2023Synthetic Datasets for Autonomous Driving: A Surveycited by 48
  25. 2023Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functionscited by 43
  26. 2022Density-preserving Deep Point Cloud Compressioncited by 39
  27. 20254D LangSplat: 4D Language Gaussian Splatting via Multimodal Large Language Modelscited by 35
  28. 2024AutoVFX: Physically Realistic Video Editing from Natural Language Instructionscited by 27
  29. 2024PACER+: On-Demand Pedestrian Animation Controller in Driving Scenarioscited by 24
  30. 2024CoMA: Compositional Human Motion Generation with Multi-modal Agentscited by 18
  31. 2024DriveEditor: A Unified 3D Information-Guided Framework for Controllable Object Editing in Driving Scenescited by 17
  32. 2024Kubrick: Multimodal Agent Collaborations for Synthetic Video Generationcited by 16
  33. 2025FiVE: A Fine-grained Video Editing Benchmark for Evaluating Emerging Diffusion and Rectified Flow Modelscited by 15
  34. 2024LidaRF: Delving into Lidar for Neural Radiance Field on Street Scenescited by 14
  35. 2025LANGTRAJ: Diffusion Model and Dataset for Language-Conditioned Trajectory Simulationcited by 11
  36. 2025SceneCrafter: Controllable Multi-View Driving Scene Editingcited by 9
  37. 2024DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Imagescited by 4
  38. 2025DrivingGaussian++: Towards Realistic Reconstruction and Editable Simulation for Surrounding Dynamic Driving Scenescited by 4

50 most cited of 52 All 52 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment
  2. 2025LangCoop: Collaborative Driving with Language
  3. 2026HorizonForge: Driving Scene Editing with Any Trajectories and Any Vehicles
  4. 2025Talk to Your Slides: High-Efficiency Slide Editing via Language-Driven Structured Data Manipulation
  5. 2024Traffic Scene Generation from Natural Language Description for Autonomous Vehicles with Large Language Model
  6. 2026Vega: Learning to Drive with Natural Language Instructions
  7. 2025OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model
  8. 2026Unifying Language-Action Understanding and Generation for Autonomous Driving