摘要\quad 我们提出了 LSeg,一种用于语言驱动的语义图像分割的新模型。 LSeg 使用文本编码器计算给定的输入标签(例如,“草”或“建筑物”)的编码和使用图像编码器计算输入图像的每个像素的编码。图像编码器使…
LANGUAGE-DRIVEN SEMANTIC SEGMENTATION论文阅读笔记 摘要 文章的主要贡献是提出了一种新的语言驱动的分割模型LSeg,其使用Text encoder编码描述性的输入标签,使用Image encoder计算图像的逐像素的embedding。图像编码器使用的是对比目标训练,目的是将像素的embedding与对应文本标签的embedding进行对齐。text embedding提供了灵活的...
Language-driven Semantic Segmentationopenreview.net/forum?id=RriDjddCLN 摘要 提出了一种新的语言驱动的语义图像分割模型LSeg。LSeg使用文本编码器与基于transformer的图像编码器一起计算描述性输入标签(例如,“草”或“建筑物”)的嵌入,该图像编码器计算输入图像的密集像素嵌入。图像编码器用一种对比目标训练,目的...
通过矩阵相乘将文本和图像结合起来了。训练时可以学到language aware(语言文本意识)的视觉特征。从而在最后推理的时候能使用文本的prompt任意的得到分割的效果。 本文中文本编码器的参数完全使用的CLIP的文本编码器的参数,因为分割任务的数据集都比较小(10-20万),为保证文本编码器的泛化性,就直接使用并锁住CLIP中文本编...
Language-driven Semantic Segmentation (LSeg) The repo contains official PyTorch Implementation of paperLanguage-driven Semantic Segmentation. ICLR 2022 Authors: Boyi Li Kilian Q. Weinberger Serge Belongie Vladlen Koltun Rene Ranftl Overview We present LSeg, a novel model for language-driven semantic imag...
Segmentation ZegFormer [42] [code] Group the pixels into segments and preforms zero-shot classification task on the segments. LSeg [186] [code] Propose language-driven semantic segmentation by matching pixel and text embeddings. SSIW [187] Introduce a test-time augmentation technique to refine the...
Q., Belongie, S., et al.: Language-driven Semantic Segmentation. arXiv (2022) Li, X. L., Liang, P.: Prefix-tuning: optimizing continuous prompts for generation. arXiv (2021) Lee, D., Song, S., Suh, J., et al.: Read-only prompt optimization for vision-language few-shot ...
LSeg: Language-driven Semantic Segmentation ICLR 2022 Code ZSSeg: A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language Model ECCV 2022 Code OpenSeg: Scaling Open-Vocabulary Image Segmentation with Image-Level Labels ECCV 2022 Code Fusioner: Open-vocabulary Semantic...
This large number of class categories also induces a large natural class imbalance, both of which are challenging for existing 3D semantic segmentation methods. To learn more robust 3D features in this context, we propose a language-driven pre-training method to encourage learned 3D features that ...
Segmentation ZegFormer [35] [code] Group the pixels into segments and preforms zero-shot classification task on the segments. LSeg [89] [code] Propose language-driven semantic segmentation by matching pixel and text embeddings. SSIW [187] Introduce a test-time augmentation technique to refine the...