{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/panacea-panoramic-and-controllable-video-1","title":"Panacea+: Panoramic and Controllable Video Generation for Autonomous Driving","arxiv_id":"2408.07605","date":"2024-08-14","proceeding":null,"authors":["Yuqing Wen","Yucheng Zhao","Yingfei Liu","Binyuan Huang","Fan Jia","Yanhui Wang","Chi Zhang","Tiancai Wang","Xiaoyan Sun","Xiangyu Zhang"],"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.","url_abs":"https://arxiv.org/abs/2408.07605v1","url_pdf":"https://arxiv.org/pdf/2408.07605v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"panacea-panoramic-and-controllable-video-1","repo_url":"https://github.com/wenyuqing/panacea","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"3d-object-detection","task_name":"3D Object Detection"},{"task_slug":"3d-object-tracking","task_name":"3D Object Tracking"},{"task_slug":"autonomous-driving","task_name":"Autonomous Driving"},{"task_slug":"lane-detection","task_name":"Lane Detection"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-tracking","task_name":"Object Tracking"},{"task_slug":"super-resolution","task_name":"Super-Resolution"},{"task_slug":"video-generation","task_name":"Video Generation"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2408.07605","atlas_url":"https://app.syntology.ai/?focus=2408.07605","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}