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有關 Feature-Align Network and Knowledge Distillation for Efficient Denoising. 的學術文章
Feature-align network with knowledge distillation for … - ‎Young - 9 個引述

Feature-Align Network With Knowledge Distillation for ...

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由 LD Young 著作2022被引用 9 次 — We propose an efficient neural network for RAW image denoising. Although neural network-based denoising has been extensively studied for image restoration, ...

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Feature-Align Network with Knowledge Distillation for ...

arXiv

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arXiv

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由 LD Young 著作2021被引用 9 次 — In this paper, we present a novel architecture and a suite of training techniques for high quality denoising in mobile devices.

Feature-Align Network with Knowledge Distillation for Efficient ...

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Feature-Align Network with Knowledge Distillation for Efficient Denoising Authors: Lucas D Young (Facebook)*; Fitsum Reda (Google); ...

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Feature-Align Network with Knowledge Distillation for ...

IEEE Computer Society

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由 LD Young 著作2022被引用 9 次 — In this paper, we present a novel architecture and a suite of training techniques for high quality denoising in mobile devices.

[PDF] Feature-Align Network and Knowledge Distillation for ...

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A novel network for efficient RAW denoising on mobile devices augmented with a new Feature-Align layer to attend to spatially varying noise and a new ...

Feature-Align Network with Knowledge Distillation for ...

CVF Open Access

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由 LD Young 著作被引用 2 次 — Image noise originates at the Bayer RAW domain. The observed signal of a pixel is gaussianly distributed about the noiseless intensity of the pixel.

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Feature-Align Network with Knowledge Distillation for ...

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Feature-Align Network and Knowledge Distillation for ...

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2024年9月6日 — Here, we propose a novel network for efficient RAW denoising on mobile devices. Our contributions are: (1) An efficient encoder-decoder network ...

Feature-Align Network with Knowledge Distillation for ...

OUCI

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OUCI

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Feature-Align Network with Knowledge Distillation for Efficient Denoising · Lucas D. Young · Fitsum A. Reda · Rakesh Ranjan · Jon Morton · Jun Hu · Yazhu Ling · Xiaoyu ...