Papers with large-scale image-text data
KD-VLP: Improving End-to-End Vision-and-Language Pretraining with Object Knowledge Distillation (2022.findings-naacl)
Copied to clipboard
| Challenge: | Existing vision-and-language pretraining approaches rely on external object detectors to encode images in a multi-modal transformer framework. |
| Approach: | They propose an object-aware end-to-end VLP framework which feeds image grid features from CNNs into the Transformer and learns the multi-modal representations jointly. |
| Outcome: | The proposed framework achieves competitive or superior performances on vision-language tasks. |
RWKV-CLIP: A Robust Vision-Language Representation Learner (2024.emnlp-main)
Copied to clipboard
| Challenge: | Using large image-text datasets, large-scale image-data sets have been used for visionlanguage pre-training. |
| Approach: | They propose a framework that leverages Large Language Models to combine and refine information from web-based image-text pairs, synthetic captions, and detection tags. |
| Outcome: | The proposed framework can combine and refine information from web-based image-text pairs, synthetic captions, and detection tags. |