In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation
সংরক্ষণ করুন:
| প্রকাশিত: | arXiv.org (Aug 9, 2024), p. n/a |
|---|---|
| প্রধান লেখক: | |
| অন্যান্য লেখক: | |
| প্রকাশিত: |
Cornell University Library, arXiv.org
|
| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | Citation/Abstract Full text outside of ProQuest |
| ট্যাগগুলো: |
কোনো ট্যাগ নেই, প্রথমজন হিসাবে ট্যাগ করুন!
|
| সার সংক্ষেপ: | We present lazy visual grounding, a two-stage approach of unsupervised object mask discovery followed by object grounding, for open-vocabulary semantic segmentation. Plenty of the previous art casts this task as pixel-to-text classification without object-level comprehension, leveraging the image-to-text classification capability of pretrained vision-and-language models. We argue that visual objects are distinguishable without the prior text information as segmentation is essentially a vision task. Lazy visual grounding first discovers object masks covering an image with iterative Normalized cuts and then later assigns text on the discovered objects in a late interaction manner. Our model requires no additional training yet shows great performance on five public datasets: Pascal VOC, Pascal Context, COCO-object, COCO-stuff, and ADE 20K. Especially, the visually appealing segmentation results demonstrate the model capability to localize objects precisely. Paper homepage: https://cvlab.postech.ac.kr/research/lazygrounding |
|---|---|
| আইএসএসএন: | 2331-8422 |
| সম্পদ: | Engineering Database |