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Great job! Have you tried working on image super-resolution task and how does it compare to existing work (e.g. SwinIR) ?
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Hi, the author of Deep Burst Super Resolution paper.
Thanks for this great work.
I am really interested in this model.
May I know will the training package being released?
Thanks.
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Hi, can you help me out with the inference code for super resolution of my test images, I am trying to implement your inference.py in Colab, will it work there, any particular comments or suggestions …
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Does QNN support input of dynamic dimensions, such as the width and height of input pictures are usually not fixed in super-resolution models. Any plans to implement this feature?
ONNX runtime supp…
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Create the components necessary to perform the training and inference of super-resolution task based on diffusion models. As reference, we could use approaches used in Imagen (https://imagen.research.…
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please help me
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## 論文概要
今までのDNNでの超解像やNRなどの失敗要因は手法の良し悪しじゃなくて結局「データが少ないから」ではないかという問題提起から、低解像度と高解像度のペアの大規模データセット(11421枚)をビームスプリッターを利用した治具で構築した。Microsoft。6/15に公開予定。
既存のSOTAの手法らの大幅な性能向上を確認。LRとSRのカメラ間でのレンズ違いによる様々なずれは局所…
tkuri updated
2 years ago
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## 🚀 Feature
Is there any official implementation of Point Cloud Super Resolution with Adversarial Residual Graph Networks in pytorch_geometric?
Official Code : https://github.com/wuhuikai/Point…
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**System and IINA version:**
- macOS
- IINA
**Expected behavior:**
**Actual behavior:**
Crash report:
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mpv log:
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```
**Step…