Meitu Imaging Research Institute (MT Lab) won 3 top international artificial intelligence conference awards

On May 30, the 3rd Pixel-level Video Understanding in the Wild, PVUW (hereinafter referred to as PVUW) held by CVPR2024, the top international artificial intelligence conference, announced the results of the competition. Meitu Image Research The institute (MTLab) won another award, winning runner-up in the Video Semantic Segmentation (VSS) and Complex Scene Video Object Segmentation (MOSE) tracks, and third place in the Video Panoramic Segmentation Challenge (VPS) track. This is also Meitu Image The research institute (MTLab) won awards at the CVPR conference for the third time, winning a total of 1 gold, 3 silver and 3 bronze outstanding results.

As the top event in the field of computer vision worldwide, CVPR has attracted the active participation of many top universities and scientific research institutions with its far-reaching influence. It has become a stage for displaying cutting-edge scientific research results in the global AI field and is highly regarded by academia and industry. of attention.

At the same time, the top PVUW competition focuses on the field of video understanding and is researched by authoritative experts in the industry such as Oxford University, Fudan University, Zhejiang University, Beijing University of Aeronautics and Astronautics, Beijing Jiaotong University, Amazon, Meta, etc. With its cutting-edge and challenging nature, this competition has attracted well-known universities and research institutes at home and abroad, including the University of Chinese Academy of Sciences, Institute of Automation of the Chinese Academy of Sciences, Harbin Institute of Technology, Meitu, Samsung, ZTE, etc. All leading companies participated. This year's PVUW competition includes a total of 4 tracks. In addition to the Video Semantic Segmentation Challenge (VSSChallenge) and the Video Panoramic Segmentation Challenge (VPSChallenge), there is a new Complex Scene Video Object Segmentation Challenge (MOSEChallenge) and an action description-based Directional Video Segmentation Challenge (MeViSChallenge) 2 ultra-difficulty tracks, among which the Complex Scene Video Object Segmentation Challenge (MOSEChallenge) collected the largest complex scene video object segmentation data set ComplexVideoObjectSegmentation (MOSE) , including the disappearance and reappearance of targets, inconspicuous small objects, severe occlusions, and crowded environments. It is designed to help cope with the challenges currently faced in the field of video understanding, such as background complexity, target occlusion, disappearance and reappearance, text understanding describing actions, etc., and to improve the ability to understand complex scenes and real-life scenes. The impressive results achieved by Meitu Imaging Lab (MTLab) in this competition are evidence of its long-term layout and continuous exploration in the video field. At the same time, it has also applied this cutting-edge technology to Meitu, a subsidiary of Meitu Company. Products such as Xiuxiu, Beauty Camera, Wink, and Meitu Design Studio provide users with practical functions and creative gameplay such as "Video Portrait Refinement", "AI Product Video", and "Smart Cutout", and through innovative research and development results Provide high-quality imaging and design services to our users. With the vigorous development of emerging video forms, the video industry has further developed towards diversification. Meitu Imaging Research Institute (MTLab) has also continued to increase its investment in research and development in the video field. Currently, Wink, a professional video portrait refinement tool, has won the title of video editing tool track. Second place, Kickstart has become the leader in the field of oral broadcast creation tools. As the core R&D center of Meitu, Meitu Imaging Research Institute (MTLab) will continue to focus on the research and development of cutting-edge technologies in the AI ​​field in the future, promote the implementation of AI technology, and create better AI work for users and customers through technological innovation and upgrades. flow.

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