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[CVPR 2024 🔥] Grounding Large Multimodal Model (GLaMM), the first-of-its-kind model capable of generating natural language responses that are seamlessly integrated with object segmentation masks.

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@hanoonaR and @mmaaz60 , Thank you very much for your excellent work! I am attempting to replicate the entire process of GLaMM starting from the pretraining phase, but I found...

description: glamm performs very well on semantic segmentation. I want to introduce glamm into my multi-agent workflow to solve a sub-task. My multi-agent is constructed by autogen framework. request: In...

@hanoonaR and @mmaaz60 I wish to run the automated annotation pipeline from scratch. As mentioned in #35 I try the command: `conda create --name grand_env_1 --file requirements_grand_env_1.txt` I get the...

Thank you for sharing your great work! I am trying to validate the GLaMM-RefSeg model and notice that the performance can vary significantly among different inference times (approximately +/- 1...

the demo caption is very simple, not like the detailed one in the paper, did you limit the output max length?

demo

Hello, I've successfully run the demo locally and managed to obtain output results. However, I've noticed that the quality of the output significantly differs from what is showcased in the...

I used the GLaMM-FullScope model to perform inference on a sample image and received a peculiar output. I've verified the versions of the relevant installed libraries, and they align with...

Hello Authors of GLaMM, Thank you for sharing your excellent work! This is just a notification that your online demo (https://glamm.mbzuai-oryx.ngrok.app) is not working now. Would it be possible to...

As shown in line 32 of "https://github.com/mbzuai-oryx/groundingLMM/tree/main/scripts/finetune_glamm_refsegm.sh", training requires a SAM pre-trained pth file, but it is not available in Model zoo. Please provide it. @mmaaz60