12 DAILY CVPR Thursday Poster Presentation Learned Trajectory Embedding for Subspace Clustering This work examines the scenario when multiple independent motions are present in a scene. Yaroslava proposes a method for simultaneously grouping the trajectories based on these motions and estimating the corresponding motion models for each group. This approach is particularly important for dynamic scene understanding, with applications ranging from autonomous driving to various other scenarios where distinguishing between multiple moving objects is essential. The motivation behind this work evolved naturally from Yaroslava’s PhD studies, which delved into Yaroslava Lochman is a PhD student at Chalmers University of Technology in Gothenburg, Sweden. Before her poster session this afternoon, she speaks to us about her paper, which explores the problem of motion segmentation. UKRAINE CORNER
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