As the most fundamental scene understanding tasks, object detection and segmentation
have made tremendous progress in deep learning era. Due to the expensive manual …

Abstract Referring Image Segmentation (RIS) leveraging transformers has achieved great
success on the interpretation of complex visual-language tasks. However, the quadratic …

This paper proposes LLaFS the first attempt to leverage large language models (LLMs) in
few-shot segmentation. In contrast to the conventional few-shot segmentation methods that …

This paper studies the problem of weakly open-vocabulary semantic segmentation
(WOVSS), which learns to segment objects of arbitrary classes using mere image-text pairs …

Open-vocabulary (OV) semantic segmentation has attracted increasing attention in recent
years, which aims to recognize objects in an open class set for real-world applications …

Panoramic images, capturing a 360∘ field of view (FoV), encompass omnidirectional spatial
information crucial for scene understanding. However, it is not only costly to obtain training …

Abstract Vision-Language Large Models (VLMs) recently become primary backbone of AI,
due to the impressive performance. However, their expensive computation costs, ie …

Names are essential to both human cognition and vision-language models. Open-
vocabulary models utilize class names as text prompts to generalize to categories unseen …

Recent works on open-vocabulary 3D instance segmentation show strong promise, but at
the cost of slow inference speed and high computation requirements. This high computation …

As one of the fundamental video tasks in computer vision, Open-Vocabulary Action
Recognition (OVAR) recently gains increasing attention, with the development of vision …