AGLA
Image descriptor model
Improves large vision-language models' ability to accurately describe images by combining global and local attention mechanisms.
[Arxiv 2024] AGLA: Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention
18 stars
2 watching
0 forks
Language: Python
last commit: over 1 year ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 byungkwanlee/collavo | Develops a PyTorch implementation of an enhanced vision language model | 93 |
 deepseek-ai/deepseek-vl | A multimodal AI model that enables real-world vision-language understanding applications | 2,145 |
 dvlab-research/lisa | A system that uses large language models to generate segmentation masks for images based on complex queries and world knowledge. | 1,923 |
 baaivision/eve | A PyTorch implementation of an encoder-free vision-language model that can be fine-tuned for various tasks and modalities | 246 |
 yiyangzhou/lure | Analyzing and mitigating object hallucination in large vision-language models to improve their accuracy and reliability. | 136 |
 andy971022/auto-lama | Automates object removal from images using computer vision techniques | 99 |
 yfzhang114/llava-align | Debiasing techniques to minimize hallucinations in large visual language models | 75 |
 damo-nlp-sg/vcd | An approach to reduce object hallucinations in large vision-language models by contrasting output distributions derived from original and distorted visual inputs | 222 |
 ayoolaolafenwa/pixellib | A deep learning library for image segmentation and object detection using PyTorch. | 1,054 |
 umass-foundation-model/3d-llm | Developing a Large Language Model capable of processing 3D representations as inputs | 979 |
 opengvlab/visionllm | A large language model designed to process and generate visual information | 956 |
| byungkwanlee/moai | Improves performance of vision language tasks by integrating computer vision capabilities into large language models | 314 |
 mshukor/evalign-icl | Evaluating and improving large multimodal models through in-context learning | 21 |
 algolzw/daclip-uir | This project controls vision-language models to restore degraded images in various environments and conditions. | 673 |
 uclanlp/elmo-c | Efficient Contextual Representation Learning Model with Continuous Outputs | 4 |