This repository contains PyTorch implementation of "Teach CLIP to Develop a Number Sense for Ordinal Regression (ECCV2024)".
Created by Du Yao, Zhai Qiang, Dai Weihang, Li Xiaomeng*
We utilize the code base of OrdinalCLIP. Please follow their instructions to prepare the environment and datasets.
This code is mainly based on OrdinalCLIP. Thanks to their great work.
Check out these amazing works leveraging CLIP for number problems!
- OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression (NeurIPS2022)
- DepthCLIP: Can Language Understand Depth? (ACM MM2022)
- CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model (CVPR2023)
- L2RCLIP: Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification (NeurIPS2023)
- Teach CLIP to Count to Ten (ICCV2023)
If you find this codebase helpful, please consider to cite:
@article{du2024teach,
title={Teach CLIP to Develop a Number Sense for Ordinal Regression},
author={Du, Yao and Zhai, Qiang and Dai, Weihang and Li, Xiaomeng},
journal={arXiv preprint arXiv:2408.03574},
year={2024}
}