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Great work on the paper! I have a quick question regarding the implementation. In the paper, you mentioned that several backbone networks like ViT, Swin, and ResNet were used. Could you please clarify…
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Hello, I am very interested in your work. I have some questions to ask you. After RESNET network extracts image features, I don't understand how to implement the code of the self attention layer. At p…
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Thanks for sharing the code.
I would like to know solver.prototxt for Resnet-101 or Resnet-101-semmantic.
How did you train Resnet-101 that scored like mAP(75.2), F1-O(74.4), F1-C(69.5) for coco dat…
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Hi, do you have resnet 100 pretrained model available for download? Thanks!
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the VIT model weight is reasonable but the Resnet weight outputs very random results, and always negative logits. Is the provided resnet weight correct?
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Notice that the results in paper 'Deep Cross-Modal Pojection Learning for Image-Text Matching' are:{top- 1 = 49.37%，top-10 = 79.27%}
while the results in this project are {top- 1 = 42.999%,top-10 = 6…
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As previously observed through preliminary modeling iterations, any and all models trained on the input images to predict the Continuous Target variable `CTBiomarkers.CalciumScoring.AbdominalAgatston`…
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### **Feature Area**
/area backend
/area sdk
The examples for nvidia-resnet cannot be built using existing scripts.
### **What feature would you like to see?**
Update existing nvidia-resnet o…
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I have finished the 1st step： python pose_align.py --imgfn_refer ./assets/images/ref.png --vidfn ./assets/videos/dance.mp4
and something wrong at the step：
Moviepy - Done !
Moviepy - video ready …
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May I ask how did you process the event input of the ResNet-34 backbone and Deeplabv3 decoder? What is the bin size that you set?