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- W4386083051 abstract "This paper studies the challenging problem of recovering motion from blur, also known as joint deblurring and interpolation or blur temporal super-resolution. The challenges are twofold: 1) the current methods still leave considerable room for improvement in terms of visual quality even on the synthetic dataset, and 2) poor generalization to real-world data. To this end, we propose a blur interpolation transformer (BiT) to effectively unravel the underlying temporal correlation encoded in blur. Based on multi-scale residual Swin transformer blocks, we introduce dual-end temporal supervision and temporally symmetric ensembling strategies to generate effective features for time-varying motion rendering. In addition, we design a hybrid camera system to collect the first real-world dataset of one-to-many blur-sharp video pairs. Experimental results show that BiT has a significant gain over the state-of-the-art methods on the public dataset Adobe240. Besides, the proposed real-world dataset effectively helps the model generalize well to real blurry scenarios. Code and data are available at https://github.com/zzh-tech/Bi'T." @default.
- W4386083051 created "2023-08-23" @default.
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- W4386083051 date "2023-06-01" @default.
- W4386083051 modified "2023-10-16" @default.
- W4386083051 title "Blur Interpolation Transformer for Real-World Motion from Blur" @default.
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- W4386083051 doi "https://doi.org/10.1109/cvpr52729.2023.00553" @default.
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