Vary
[ECCV 2024] Official code implementation of Vary: Scaling Up the Vision Vocabulary of Large Vision Language Models.
AI summary
Document comprehension model
An implementation of a vision vocabulary model for large language models to improve document understanding and recognition capabilities
- stars
- 1.8K
- forks
- 159
- watching
- 54
Similar projects
Found by comparing what the projects do, not just their names.
Image understanding model
A large multi-modal model developed using the Llama3 language model, designed to improve image understanding capabilities.
Text classifier
A Python package implementing an interpretable machine learning model for text classification with visualization tools
Model Interpreter
A library providing interpretability methods for TensorFlow 2.x models
interpretml/dice1.4K
Model explanations
Provides counterfactual explanations for machine learning models to facilitate interpretability and understanding.
Vision Language Model
Develops a PyTorch implementation of an enhanced vision language model
Scene understanding model
An implementation of Attend, Infer, Repeat, a method for fast scene understanding using generative models.
Language model explainer
An interactive visualization library for exploring and understanding transformer-based language models
Vision Language Integrator
Improves performance of vision language tasks by integrating computer vision capabilities into large language models
Vision-Language Model Framework
Implementing a unified modal learning framework for generative vision-language models
msracver/fcis1.6K
Instance segmentation framework
An implementation of a fully convolutional instance-aware semantic segmentation framework using CUDA.
Chart eval
An evaluation suite for assessing chart understanding in multimodal large language models.
Model evaluator
Evaluates the capabilities of large multimodal models using a set of diverse tasks and metrics
Word embedding model
A framework to learn word embeddings using lexical dictionaries
Vision-Language Model
A PyTorch implementation of an encoder-free vision-language model that can be fine-tuned for various tasks and modalities
lxtgh/omg-seg1.3K
Visual Model
Develops an end-to-end model for multiple visual perception and reasoning tasks using a single encoder, decoder, and large language model.
