Language-Driven Semantic Segmentation. Contribute to isl-org/lang-seg development by creating an account on GitHub.
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…
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...
Language-driven semantic seg- mentation. In International Conference on Learning Repre- sentations, 2022. [39] Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, and Steven C.H. Hoi. Align and prompt: Video-and-language pre-training with entity prompts. In 2022 ...
Semantic CLIPSeg [103] [code] Extend CLIP by introducing a lightweight transformer-based decoder. 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...
3D open-vocabulary semantic segmentation is a challenge in the task of 3D scene understanding, as most current models trained on closed-set datasets struggle to effectively identify categories that were not seen during training. To address this, we introduce a framework called LSWKD. It distills ...
语义分割(Semantic Segmentation)的目的是为图像中的每个像素分配一个类别标签。预先训练好的 VLM 通过比较给定图像像素和文本的嵌入,实现分割任务的Zero-shot预测。 物体检测(Object Detection)的目的是对图像中的物体进行定位和分类,这对各种视觉应用都很重要。利用从辅助数据集中学习到的物体定位能力,预训练 VLM 通过...
‘Confirming the robustness of neuronal response across participants’) and Extended Data Fig.2c–f), indicating that the results were not driven by any single participant or a small subset of participants. We also evaluated the consistency of semantic representations in the three participants who...
This symmetric processing can better understand semantic information and improve the overall performance of VG systems. Additionally, we design a language-driven, multi-stage cross-modal decoder in the decoder section to iteratively locate targets based on language information, thereby increasing the ...
which represents the importance of a term in a document relative to a corpus. Vectorizers capture the lexical information of the text but may not capture semantic relationships between words. Word embedding is a more advanced vectorization technique that captures semantic relationships between words by...