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Towards Training-free Open-world Segmentation via Image Prompt Foundation Models
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Towards Training-free Open-world Segmentation via Image Prompt Foundation Models

Lv Tang
Peng-Tao Jiang
Haoke Xiao
Bo Li
    VLM
ArXiv (abs)PDFHTML

Papers citing "Towards Training-free Open-world Segmentation via Image Prompt Foundation Models"

3 / 3 papers shown
Title
SynPo: Boosting Training-Free Few-Shot Medical Segmentation via High-Quality Negative Prompts
SynPo: Boosting Training-Free Few-Shot Medical Segmentation via High-Quality Negative Prompts
Yufei Liu
Haoke Xiao
Jiaxing Chai
Yongcun Zhang
Rong Wang
Zijie Meng
Zhiming Luo
MedImVLM
13
0
0
18 Jun 2025
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects
Guohuan Xie
Syed Ariff Syed Hesham
Wenya Guo
Bing Li
Ming-Ming Cheng
Guolei Sun
Yun-Hai Liu
26
0
0
16 Jun 2025
Context-aware Feature Generation for Zero-shot Semantic Segmentation
Context-aware Feature Generation for Zero-shot Semantic Segmentation
Zhangxuan Gu
Siyuan Zhou
Li Niu
Zihan Zhao
Liqing Zhang
VLM
146
140
0
16 Aug 2020

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