no code implementations • 21 May 2023 • Mengyin Liu, Chao Zhu, Shiqi Ren, Xu-Cheng Yin
1) Firstly, Semantic-aware Iterative Segmentation (SIS) is proposed to extract unsupervised representations of multi-view images, which are converted into 2D pedestrian masks as pseudo labels, via our proposed iterative PCA and zero-shot semantic classes from vision-language models.
1 code implementation • CVPR 2023 • Mengyin Liu, Jie Jiang, Chao Zhu, Xu-Cheng Yin
Firstly, we propose a self-supervised Vision-Language Semantic (VLS) segmentation method, which learns both fully-supervised pedestrian detection and contextual segmentation via self-generated explicit labels of semantic classes by vision-language models.
Ranked #5 on Pedestrian Detection on Caltech
no code implementations • 15 Jul 2022 • Mengyin Liu, Chao Zhu, Hongyu Gao, Weibo Gu, Hongfa Wang, Wei Liu, Xu-Cheng Yin
2) Secondly, a text-guided information range minimization method is proposed to adaptively encode descriptive parts of each modality into an identical space with a powerful pretrained linguistic model.