8 citations · 8 across the 2 of their papers we have counts for
4 papers · 1 filter
Omnimatte: Associating Objects and Their Effects in Video
Erika Lu, Forrester Cole, Tali Dekel +3
Computer vision is increasingly effective at segmenting objects in images and videos; however, scene effects related to the objects -- shadows, reflections, generated smoke, etc --…
Self-supervised Video Object Segmentation by Motion Grouping
Charig Yang, Hala Lamdouar, Erika Lu +2
Animals have evolved highly functional visual systems to understand motion, assisting perception even under complex environments. In this paper, we work towards developing a comput…
MAST: A Memory-Augmented Self-supervised Tracker
Zihang Lai, Erika Lu, Weidi Xie
Recent interest in self-supervised dense tracking has yielded rapid progress, but performance still remains far from supervised methods. We propose a dense tracking model trained o…
Class-Agnostic Counting
Erika Lu, Weidi Xie, Andrew Zisserman
Nearly all existing counting methods are designed for a specific object class. Our work, however, aims to create a counting model able to count any class of object. To achieve this…