Redirecting to original paper in 30 seconds...
Click below to go immediately or wait for automatic redirect
📄 Abstract
Abstract: Current video representations heavily rely on unstable and over-grained
priors for motion and appearance modelling, \emph{i.e.}, pixel-level matching
and tracking. A tracking error of just a few pixels would lead to the collapse
of the visual object representation, not to mention occlusions and large motion
frequently occurring in videos. To overcome the above mentioned vulnerability,
this work proposes spatio-temporally consistent proxy nodes to represent
dynamically changing objects/scenes in the video. On the one hand, the
hierarchical proxy nodes have the ability to stably express the multi-scale
structure of visual objects, so they are not affected by accumulated tracking
error, long-term motion, occlusion, and viewpoint variation. On the other hand,
the dynamic representation update mechanism of the proxy nodes adequately
leverages spatio-temporal priors of the video to mitigate the impact of
inaccurate trackers, thereby effectively handling drastic changes in scenes and
objects. Additionally, the decoupled encoding manner of the shape and texture
representations across different visual objects in the video facilitates
controllable and fine-grained appearance editing capability. Extensive
experiments demonstrate that the proposed representation achieves high video
reconstruction accuracy with fewer parameters and supports complex video
processing tasks, including video in-painting and keyframe-based temporally
consistent video editing.
Key Contributions
This paper introduces a novel video representation using hierarchical, spatio-temporally consistent proxy nodes that are robust to tracking errors, occlusions, and large motions. This approach enables stable representation of multi-scale object structures and facilitates easier video editing by providing a more reliable underlying representation.
Business Value
Enabling more stable and editable video representations can revolutionize video editing software, content creation pipelines, and video analysis tools, making them more robust and user-friendly.