Cat Paper Collection
As reported by Cisco, 90% of net traffic will be visual, and indeed, most of the visual data are cat photos and videos. Thus, understanding, modeling, and synthesizing our feline friends becomes a more and more critical research problem these days, especially for our cat lovers.
Cat Paper Collection is an academic paper collection that includes computer graphics, computer vision, and machine learning papers that produce experimental results related to cats. If you want to add/remove an article, please send an email to Jun-Yan Zhu (junyanz at cs dot cmu dot edu). We thank all the authors for their contribution and support.
 |
Efficient Halftoning via Deep Reinforcement Learning Haitian Jiang, Dongliang Xiong, Xiaowen Jiang, Li Ding, Liang Chen, Kai Huang In IEEE TIP 2023 [Paper] |
 |
A Markovian framework for digital halftoning Robert Geist, Robert Reynolds, Darrell Suggs In ACM Transactions on Graphics (TOG) 1993 [Paper] |
Last updated in Jan 2026