activity
20202025
most citedBetrayed by Motion: Camouflaged Object Discovery via Motion Segmentation

8 citations · 14 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Reading Recognition in the Wild

Charig Yang, Samiul Alam, Shakhrul Iman Siam +12

To enable egocentric contextual AI in always-on smart glasses, it is crucial to be able to keep a record of the user's interactions with the world, including during reading. In thi…

cs.CV2024

Made to Order: Discovering monotonic temporal changes via self-supervised video ordering

Charig Yang, Weidi Xie, Andrew Zisserman

Our objective is to discover and localize monotonic temporal changes in a sequence of images. To achieve this, we exploit a simple proxy task of ordering a shuffled image sequence,…

cs.CV2024★ 1 cited

Moving Object Segmentation: All You Need Is SAM (and Flow)

Junyu Xie, Charig Yang, Weidi Xie +1

The objective of this paper is motion segmentation -- discovering and segmenting the moving objects in a video. This is a much studied area with numerous careful, and sometimes com…

cs.CV2021

It's About Time: Analog Clock Reading in the Wild

Charig Yang, Weidi Xie, Andrew Zisserman

In this paper, we present a framework for reading analog clocks in natural images or videos. Specifically, we make the following contributions: First, we create a scalable pipeline…

cs.CV2021★ 5 cited

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…

cs.CV2020★ 8 cited

Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation

Hala Lamdouar, Charig Yang, Weidi Xie +1

The objective of this paper is to design a computational architecture that discovers camouflaged objects in videos, specifically by exploiting motion information to perform object…