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Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories
arXiv:2604.09429v4 Announce Type: replace Abstract: Recovering camera parameters from images and rendering scenes from novel viewpoints have been treated as separate tasks in computer vision and graphics. This separation breaks down when image coverage is sparse or poses are ambiguous, since each task depends on what the other produces.
MotionEnhancer: Leveraging Video Diffusion for Motion-Enhanced Vision-Language Models
arXiv:2606.06853v1 Announce Type: new Abstract: The new era has witnessed a remarkable capability to extend Vision-Language Models (VLMs) for tackling tasks of video understanding. While current VLMs excel at event- or story-level understanding, their ability to capture fine-grained motion details remains limited, primarily due to their focus on high-level static semantic structures and macro-event logic. In contrast, Video Diffusion Models (VDMs) are adept at modeling dynamic motion...