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DiffMatch: Visual-Language Guidance Makes Better Semi-supervised Change Detector
May 9, 2024, 4:44 a.m. | Kaiyu Li, Xiangyong Cao, Yupeng Deng, Deyu Meng
cs.CV updates on arXiv.org arxiv.org
Abstract: Change Detection (CD) aims to identify pixels with semantic changes between images. However, annotating massive numbers of pixel-level images is labor-intensive and costly, especially for multi-temporal images, which require pixel-wise comparisons by human experts. Considering the excellent performance of visual language models (VLMs) for zero-shot, open-vocabulary, etc. with prompt-based reasoning, it is promising to utilize VLMs to make better CD under limited labeled data. In this paper, we propose a VLM guidance-based semi-supervised CD method, …
abstract arxiv change cs.cv detection etc experts guidance however human identify images labor language language models massive numbers performance pixel pixels semantic semi semi-supervised temporal type visual visual language models vlms wise zero-shot
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