Dynamic Camera Poses and Where to Find Them

• URL: http://arxiv.org/abs/2504.17788v1
• Date: Thu, 24 Apr 2025 17:59:56 GMT
• Title: Dynamic Camera Poses and Where to Find Them
• Authors: Chris Rockwell, Joseph Tung, Tsung-Yi Lin, Ming-Yu Liu, David F. Fouhey, Chen-Hsuan Lin,
• Abstract summary: We introduce DynPose-100K, a large-scale dataset of dynamic Internet videos annotated with camera poses.<n>For pose estimation, we combine the latest techniques of point tracking, dynamic masking, and structure-from-motion.<n>Our analysis and experiments demonstrate that DynPose-100K is both large-scale and diverse across several key attributes.
• Score: 36.249380390918816
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Annotating camera poses on dynamic Internet videos at scale is critical for advancing fields like realistic video generation and simulation. However, collecting such a dataset is difficult, as most Internet videos are unsuitable for pose estimation. Furthermore, annotating dynamic Internet videos present significant challenges even for state-of-theart methods. In this paper, we introduce DynPose-100K, a large-scale dataset of dynamic Internet videos annotated with camera poses. Our collection pipeline addresses filtering using a carefully combined set of task-specific and generalist models. For pose estimation, we combine the latest techniques of point tracking, dynamic masking, and structure-from-motion to achieve improvements over the state-of-the-art approaches. Our analysis and experiments demonstrate that DynPose-100K is both large-scale and diverse across several key attributes, opening up avenues for advancements in various downstream applications.

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