Panacea+: Panoramic and Controllable Video Generation for Autonomous Driving

• URL: http://arxiv.org/abs/2408.07605v1
• Date: Wed, 14 Aug 2024 15:10:13 GMT
• Title: Panacea+: Panoramic and Controllable Video Generation for Autonomous Driving
• Authors: Yuqing Wen, Yucheng Zhao, Yingfei Liu, Binyuan Huang, Fan Jia, Yanhui Wang, Chi Zhang, Tiancai Wang, Xiaoyan Sun, Xiangyu Zhang,
• Abstract summary: We propose Panacea+, a powerful framework for generating video data in driving scenes. Panacea+ adopts a multi-view appearance noise prior mechanism and a super-resolution module for enhanced consistency and increased resolution. Experiments show that the generated video samples greatly benefit a wide range of tasks on different datasets.
• Score: 23.63374916271247
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

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