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### Feature request / 功能建议
Hi, I've found the support of the downstream task, referring expression comprehension (REC)
and the model in HF, THUDM/cogvlm-grounding-generalist-hf
Want to ask if ther…
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Hi, authors
Thanks a lot for your excellent job. I wonder do you have the plan to test the model on referring expression comprehension task? Since it is a more fine-grained task, which may gain mor…
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Hi,
Thanks for sharing the great work. I ran the inference code for referring expression comprehension, but it looks like the numbers I got do not match what's reported here on RefCOCO+/g, althoug…
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# MAttNet: Modular Attention Network for Referring Expression Comprehension
Original paper:
[MAttNet: Modular Attention Network for Referring Expression Comprehension](http://openaccess.thecvf.co…
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Really nice work! Could the author also provide the hyperparameters used for training the phi-3 mini backbone (i.e., pretrain.sh and finetune_lora.sh)?
In addition, during my training process, I n…
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# Specification Features
## Main elements
- Type: Modular Integer
- Type: Range Integer
- Type: Enumeration
- Type: Enumeration (always valid)
- Type: Boolean
- Type: Message
- Type: Deriv…
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The paper mentioned referring expression comprehension (REC) - a vital task that measures the language-driven grounding ability of a visual-language multimodal model. RefCOCO/+/g are also used for tra…
tydia updated
7 months ago
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Full name of submitter (unless configured in github; will be published with the issue): Jim X
[class.cdtor] p1 says
> For an object with a non-trivial constructor, **referring to** any non-static …
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Hi All:
MMDetection supports Grounding-DINO inference and fine-tuning for now. The mAP we achieved in our reproduction is higher than the official results. We also provide the results of retraining …
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I use your released code to train dga model on the environment of python3 and torch 1.7. Then, i used the trained paratmeters to test your released dataset(test_expressions.json), the accuracy is 53.…