2 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CV2025
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…
cs.CL2024★ 1 cited
Unchosen Experts Can Contribute Too: Unleashing MoE Models' Power by Self-Contrast
Chufan Shi, Cheng Yang, Xinyu Zhu +6
Mixture-of-Experts (MoE) has emerged as a prominent architecture for scaling model size while maintaining computational efficiency. In MoE, each token in the input sequence activat…
cs.CV2023★ 2 cited
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…