Dynamic Camera Poses and Where to Find Them
Authors: name: Chris Rockwell, name: Joseph Tung, name: Tsung-Yi Lin, name: Ming-Yu Liu, name: David F. Fouhey, name: Chen-Hsuan Lin

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.