CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching-Reference-Cited by-同舟云学术

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CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
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Author:

Wu Xiaoshi¹,Zhu Feng²,Zhao Rui²,Li Hongsheng¹

Affiliation:

1. The Chinese University of Hong Kong,Multimedia Laboratory

2. SenseTime Research

Funder

National Key R&D Program of China

Innovation and Technology Commission (ITC)'s InnoHK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203675.pdf?arnumber=10203675

Reference43 articles.

1. Exploring visual prompts for adapting large-scale models;Bahng;arXiv preprint,2022

2. Visual prompting: Modifying pixel space to adapt pre-trained models;Bahng;ArXiv,2022

3. Zero-Shot Object Detection

4. Language models are few-shot learners;Brown;ArXiv,2020

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1. VLM-guided Explicit-Implicit Complementary novel class semantic learning for few-shot object detection;Expert Systems with Applications;2024-12

2. Contextual Object Detection with Multimodal Large Language Models;International Journal of Computer Vision;2024-08-20

3. Single-stage zero-shot object detection network based on CLIP and pseudo-labeling;International Journal of Machine Learning and Cybernetics;2024-08-20

4. Towards Open Vocabulary Learning: A Survey;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-07

5. OV-VG: A benchmark for open-vocabulary visual grounding;Neurocomputing;2024-07

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