馃 Introduction Traditional image classification models need to be trained on a fixed set of labeled classes. But what if we could classify new images into any category we want, without retraining the model? That鈥檚 where zero-shot classification come...

Zero-Shot Image Matting: Time for a New Perspective In this article, we're taking a deep dive into "Zim: Zero-Shot Image Matting For Anything," a groundbreaking approach presented by a group of researchers from NAVER Cloud and various institutions. T...

Arxiv: https://arxiv.org/abs/2411.07184v1 PDF: https://arxiv.org/pdf/2411.07184v1.pdf Authors: Xihui Liu, Yan-Pei Cao, Edmund Y. Lam, Xiaoyang Wu, Liangjun Lu, Yuan-Chen Guo, Yukun Huang, Yunhan Yang Published: 2024-11-11 Exploring 3D part segmenta...

Arxiv: https://arxiv.org/abs/2411.07184v1 PDF: https://arxiv.org/pdf/2411.07184v1.pdf Authors: Xihui Liu, Yan-Pei Cao, Edmund Y. Lam, Xiaoyang Wu, Liangjun Lu, Yuan-Chen Guo, Yukun Huang, Yunhan Yang Published: 2024-11-11 Understanding the vast uni...

I. Introduction Zero-shot learning (ZSL) is a machine learning paradigm that enables models to classify new examples that are not included in the training data. In Zero-Shot Learning, the model uses previously learned information to recognize new cla...
