Summary of Just a Few Glances: Open-set Visual Perception with Image Prompt Paradigm, by Jinrong Zhang et al.
Just a Few Glances: Open-Set Visual Perception with Image Prompt Paradigm
by Jinrong Zhang, Penghui Wang, Chunxiao Liu, Wei Liu, Dian Jin, Qiong Zhang, Erli Meng, Zhengnan Hu
First submitted to arxiv on: 14 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed novel prompt paradigm in Open-Set Object Detection (OSOD) and Open-Set Segmentation (OSS), the Image Prompt Paradigm, enables detection or segmentation of specialized categories without multi-round human intervention. This paradigm uses just a few image instances as prompts and proposes a novel framework, MI Grounding, for automatic encoding, selection, and fusion. The framework achieves single-stage and non-interactive inference. Experiments on public datasets show that MI Grounding achieves competitive performance compared to text prompt paradigm methods and visual prompt paradigm methods, while outperforming existing methods on the constructed specialized ADR50K dataset. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Open-Set Object Detection (OSOD) and Open-Set Segmentation (OSS) are exciting areas of research. The idea is to use images as prompts instead of text or other methods. This helps machines understand what they should detect or segment without needing human interaction. The new approach, called MI Grounding, uses just a few image examples to make decisions. It’s like teaching a machine to recognize objects by showing it some examples, and then letting it figure out what those objects are on its own. The results show that this method works well and is better than other approaches in certain situations. |
Keywords
» Artificial intelligence » Grounding » Inference » Object detection » Prompt
