Apr 16, 2024 · We propose Category Search from External Databases (CaSED), a training-free method that leverages a pre-trained vision-language model and an external database.
Code implementation of our paper: Vocabulary-free Image Classification and Semantic Segmentation. License: MIT license. 4 stars. 1 fork.
Feb 15, 2024 · This paper presents a novel task, Vocabulary-free Image Classification, where semantic categories need to be automatically mined. This is important when ...
The Vocabulary-free Image Classification (VIC) task, which aims to assign a class from an unconstrained language-induced semantic space to an input image ...
CaSED first extracts a set of candidate categories from captions retrieved from the database based on their semantic similarity to the image, and then assigns ...
We thus formalize a novel task, termed as Vocabulary-free Image Classification (VIC), where we aim to assign to an input image a class that resides in an ...
May 30, 2024 · A novel task, termed as Vocabulary-free Image Classification (VIC), where we aim to assign to an input image a class that resides in an unconstrained language- ...
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A novel task, termed as Vocabulary-free Image Classification (VIC), where we aim to assign to an input image a class that resides in an unconstrained language- ...
Missing: Segmentation. | Show results with:Segmentation.
Unsupervised Open-Vocabulary Semantic Segmentation aims to segment an image into regions referring to an ar- bitrary set of concepts described by text, ...
In this paper, we propose FreeSeg, a generic framework to accomplish Unified, Universal and Open-Vocabulary Image Segmentation.