Multi-Scale Memory-Based Video Deblurring

• URL: http://arxiv.org/abs/2204.02977v1
• Date: Wed, 6 Apr 2022 08:48:56 GMT
• Title: Multi-Scale Memory-Based Video Deblurring
• Authors: Bo Ji and Angela Yao
• Abstract summary: We design a memory branch to memorize the blurry-sharp feature pairs in the memory bank. To enrich the memory of our memory bank, we also designed a bidirectional recurrency and multi-scale strategy. Experimental results demonstrate that our model outperforms other state-of-the-art methods.
• Score: 34.488707652997704
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Video deblurring has achieved remarkable progress thanks to the success of deep neural networks. Most methods solve for the deblurring end-to-end with limited information propagation from the video sequence. However, different frame regions exhibit different characteristics and should be provided with corresponding relevant information. To achieve fine-grained deblurring, we designed a memory branch to memorize the blurry-sharp feature pairs in the memory bank, thus providing useful information for the blurry query input. To enrich the memory of our memory bank, we further designed a bidirectional recurrency and multi-scale strategy based on the memory bank. Experimental results demonstrate that our model outperforms other state-of-the-art methods while keeping the model complexity and inference time low. The code is available at https://github.com/jibo27/MemDeblur.

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