Charig Yang — accepted AI-conference papers

2026

ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models

Jonathan Roberts, Mohammad Reza Taesiri, Ansh Sharma, Akash Gupta, Samuel Roberts, Ioana Croitoru +27

ICML 2026poster

Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children or animals. Despite this, they attain high scores on many popular visual benchmarks, with headroom rapidly eroded by surging model progress. To address …

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2025

Reading Recognition in the Wild

Charig Yang, Samiul Alam, Shakhrul Iman Siam, Michael J. Proulx, Lambert Mathias, Kiran Somasundaram +9

NeurIPS 2025poster

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 this paper, we introduce a new task of reading recognition to determine when the user is reading. We first introduce the fi…

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2022

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

Charig Yang, Weidi Xie, Andrew Zisserman

CVPR 2022poster

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 for generating synthetic clocks, significantly reducing the requirements for the labour-intensive annotations; Second,…

Cited by 15 PDF ↗code ↗Scholar ↗

2021

Self-Supervised Video Object Segmentation by Motion Grouping

Charig Yang, Hala Lamdouar, Erika Lu, Andrew Zisserman, Weidi Xie

ICCV 2021poster

Animals have evolved highly functional visual systems to understand motion, assisting perception even under complex environments. In this paper, we work towards developing a computer vision system able to segment objects by exploiting motion cues, i.e. motion segmentation. To achieve this, we introd…

Cited by 185 PDF ↗Scholar ↗