mlsanityData to 7 Oct 2026

Panacea+: Panoramic and Controllable Video Generation for Autonomous Driving

arXiv 2408.07605 ↗First posted 14 Aug 2024cs.CVcited by 5

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Abstract (arXiv)

The field of autonomous driving increasingly demands high-quality annotated video training data. In this paper, we propose Panacea+, a powerful and universally applicable framework for generating video data in driving scenes. Built upon the foundation of our previous work, Panacea, Panacea+ adopts a multi-view appearance noise prior mechanism and a super-resolution module for enhanced consistency and increased resolution. Extensive experiments show that the generated video samples from Panacea+ greatly benefit a wide range of tasks on different datasets, including 3D object tracking, 3D object detection, and lane detection tasks on the nuScenes and Argoverse 2 dataset. These results strongly prove Panacea+ to be a valuable data generation framework for autonomous driving.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 67 of its 85 references that are in the map. First posted on arXiv 14 Aug 2024.

Builds on

67 of 85 references.

References · 67

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38 more
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Cited by year

Citing papers per year: 2024: 2; 2025: 3.

5 papers.

  1. 20253D and 4D World Modeling: A Surveycited by 64
  2. 2024Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Modelcited by 14
  3. 2025MObI: Multimodal Object Inpainting Using Diffusion Modelscited by 4
  4. 2025Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Drivingcited by 2
  5. 2024LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulationcited by 0