5 papers
Stepping Out of Similar Semantic Space for Open-Vocabulary Segmentation
Yong Liu, SongLi Wu, Sule Bai +3
Open-vocabulary segmentation aims to achieve segmentation of arbitrary categories given unlimited text inputs as guidance. To achieve this, recent works have focused on developing…
DreamLight: Towards Harmonious and Consistent Image Relighting
Yong Liu, Wenpeng Xiao, Qianqian Wang +5
We introduce a model named DreamLight for universal image relighting in this work, which can seamlessly composite subjects into a new background while maintaining aesthetic uniform…
Fast Omni-Directional Image Super-Resolution: Adapting the Implicit Image Function with Pixel and Semantic-Wise Spherical Geometric Priors
Xuelin Shen, Yitong Wang, Silin Zheng +3
In the context of Omni-Directional Image (ODI) Super-Resolution (SR), the unique challenge arises from the non-uniform oversampling characteristics caused by EquiRectangular Projec…
Open-Vocabulary Segmentation with Semantic-Assisted Calibration
Yong Liu, Sule Bai, Guanbin Li +2
This paper studies open-vocabulary segmentation (OVS) through calibrating in-vocabulary and domain-biased embedding space with generalized contextual prior of CLIP. As the core of…
Universal Segmentation at Arbitrary Granularity with Language Instruction
Yong Liu, Cairong Zhang, Yitong Wang +3
This paper aims to achieve universal segmentation of arbitrary semantic level. Despite significant progress in recent years, specialist segmentation approaches are limited to speci…