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PeterWang512 / GenDataAttribution

Evaluating Data Attribution for Text-to-Image Models: a visual data attribution benchmark for evaluating and learning training image influences.
https://peterwang512.github.io/GenDataAttribution
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Questions about the mapper weight #2

Open kaoshizhou opened 1 year ago

kaoshizhou commented 1 year ago

Hi author,

Thanks for your wonderful work!

I have downloaded the mapper weights from here, and I found that there is only one weight file for each image encoder. I would like to sincerely ask, does this weight file represent the "Object+Style" model in the paper?

If so, would you release the "Object-Centric" and "Artist-Style" models in the near future? I'm very interested in performance comparisons between models fine-tuned on different sets (e.g., DINO Object-Centric outperforms DINO Object + Style on style Recall@10 as shown in Figure 5 in the paper, which is a bit counterintuitive).

Thanks again for your contribution to the community! Looking forward to your reply.

PeterWang512 commented 11 months ago

Hi,

Sorry for the late response. Yes, the weight files are all "Object+Style" models. I also updated the repo so that the "Object-Centric" and "Artist-Style" models can be downloaded by running bash weights/download_style_object_ablation.sh. You might need to git pull the latest version of the repo. Thanks!