2 citations · 2 across the 4 of their papers we have counts for
4 papers
CharGen: High Accurate Character-Level Visual Text Generation Model with MultiModal Encoder
Lichen Ma, Tiezhu Yue, Pei Fu +4
Recently, significant advancements have been made in diffusion-based visual text generation models. Although the effectiveness of these methods in visual text rendering is rapidly…
EOV-Seg: Efficient Open-Vocabulary Panoptic Segmentation
Hongwei Niu, Jie Hu, Jianghang Lin +2
Open-vocabulary panoptic segmentation aims to segment and classify everything in diverse scenes across an unbounded vocabulary. Existing methods typically employ two-stage or singl…
HyperSeg: Towards Universal Visual Segmentation with Large Language Model
Cong Wei, Yujie Zhong, Haoxian Tan +4
This paper aims to address universal segmentation for image and video perception with the strong reasoning ability empowered by Visual Large Language Models (VLLMs). Despite signif…
Depth-Guided Semi-Supervised Instance Segmentation
Xin Chen, Jie Hu, Xiawu Zheng +3
Semi-Supervised Instance Segmentation (SSIS) aims to leverage an amount of unlabeled data during training. Previous frameworks primarily utilized the RGB information of unlabeled i…