and long-range motion representation that allows for tracking through occlusions and modeling full-length trajectories. This method finds correspondences between frames, a fundamental problem in computer vision. These correspondences are the foundation for various applications, notably dynamic 3D scene reconstruction, as understanding 2D correspondences between frames in a dynamic scene is essential for reconstructing its 3D geometry and 3D motion. The research also opens up exciting possibilities for video editing, allowing for seamless propagation of edits across multiple frames. “I came up with this idea because, in my last project, I realized there was no such motion representation in the past,” Qianqian tells us. “It’s not a new problem, but people don’t have a good solution. The last paper I saw similar to our work was 10 years ago, but because it’s too challenging, and people don’t have new tools to work on it, progress has been suspended for a decade.” Now, renewed interest in this problem has sparked concurrent research. While approaches may differ, the shared goal remains the same – tracking points in a video 4 DAILY ICCV Friday Oral Presentation
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