Exploring Open-Vocabulary Semantic Segmentation without Human Labels

1 June 2023

Papers citing "Exploring Open-Vocabulary Semantic Segmentation without Human Labels"

6 / 6 papers shown

Title
Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation Tong Shao Zhuotao Tian Hang Zhao Jingyong Su VLM 39 15 0 11 Jul 2024
GroupViT: Semantic Segmentation Emerges from Text Supervision Jiarui Xu Shalini De Mello Sifei Liu Wonmin Byeon Thomas Breuel Jan Kautz Xinyu Wang ViT VLM 189 499 0 22 Feb 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 305 7,443 0 11 Nov 2021
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer Zhihe Lu Sen He Xiatian Zhu Li Zhang Yi-Zhe Song Tao Xiang ViT 171 173 0 06 Aug 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 317 5,785 0 29 Apr 2021
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts Soravit Changpinyo P. Sharma Nan Ding Radu Soricut VLM 290 1,084 0 17 Feb 2021