R2D2
Vision-Language Framework
A framework for large-scale cross-modal benchmarks and vision-language tasks in Chinese
157 stars
2 watching
23 forks
Language: Python
last commit: over 1 year ago Related projects:
Repository | Description | Stars |
---|---|---|
| Develops a multimodal task and dataset to assess vision-language models' ability to handle interleaved image-text inputs. | 33 |
| A deep learning framework for iteratively decomposing vision and language reasoning via large language models. | 32 |
| Implementing a unified modal learning framework for generative vision-language models | 43 |
| An end-to-end image captioning system that uses large multi-modal models and provides tools for training, inference, and demo usage. | 1,849 |
| Develops and trains models for vision-language learning with decoupled language pre-training | 24 |
| A computer vision framework for robotics applications that simplifies the creation of vision systems and generates code in multiple programming languages. | 380 |
| An annotated preference dataset and training framework for improving large vision language models. | 88 |
| A deep learning framework for training multi-modal models with vision and language capabilities. | 1,299 |
| Pre-trains a multilingual model to bridge vision and language modalities for various downstream applications | 279 |
| An open-source software framework for building modular electro-optical projects with interchangeable components | 468 |
| Improves performance of vision language tasks by integrating computer vision capabilities into large language models | 314 |
| A lightweight deep learning framework for real-time semantic segmentation | 514 |
| A demo project demonstrating the integration of Core ML and Vision Framework with Swift 4 for image classification using an Inception V3 network. | 217 |
| This is an open-source project that proposes a novel method to train large-scale vision-language models with minimal resources and no fine-tuning required. | 94 |
| A framework for grounding language models to images and handling multimodal inputs and outputs | 478 |