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电商网站建设与运营成本,pc 移动端网站建设,哪建网站好,内蒙古创意网站开发目录 CVPR 2023图像超分任意尺度超分盲超分 视频超分特殊场景 总结参考资料 CVPR 2023 官网链接：https://cvpr2023.thecvf.com/ 会议时间：2023年6月18日-6月22日，加拿大温哥华 CVPR 2023统计数据： 提交：9155篇论文接…

目录

  • CVPR 2023
    • 图像超分
      • 任意尺度超分
      • 盲超分
    • 视频超分
    • 特殊场景
  • 总结
  • 参考资料

CVPR 2023

官网链接：https://cvpr2023.thecvf.com/
会议时间：2023年6月18日-6月22日，加拿大温哥华
CVPR 2023统计数据：

  • 提交：9155篇论文
  • 接受：2359篇论文（25.8%的接受率）
  • 亮点：235篇论文（占录取论文的10%，占提交论文的2.6%）
  • 获奖候选人：12篇论文（占录取论文的0.51%，占提交论文的0.13%）

现将超分辨率方向上接收的论文汇总如下，遗漏之处还请大家斧正。

图像超分

  1. N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution
    • Paper: https://arxiv.org/abs/2211.11436
    • Code: https://github.com/rami0205/NGramSwin
    • Keywords: Transformer, Lightweight
  2. Perception-Oriented Single Image Super-Resolution using Optimal Objective Estimation
    • Paper: https://arxiv.org/abs/2211.13676
    • Code: https://github.com/seungho-snu/SROOE
  3. Activating More Pixels in Image Super-Resolution Transformer
    • Paper: https://arxiv.org/abs/2205.04437
    • Code: https://github.com/XPixelGroup/HAT
    • Keywords: Transformer
  4. Burstormer: Burst Image Restoration and Enhancement Transformer
    • Paper: https://arxiv.org/abs/2304.01194
    • Code: http://github.com/akshaydudhane16/Burstormer
    • Keywords: Burst super-resolution
  5. Generative Diffusion Prior for Unified Image Restoration and Enhancement
    • Paper: https://arxiv.org/abs/2304.01247
    • Keywords: Unified image recovery
  6. Tunable Convolutions with Parametric Multi-Loss Optimization
    • Paper: https://arxiv.org/abs/2304.00898
  7. Omni Aggregation Networks for Lightweight Image Super-Resolution
    • Paper: https://arxiv.org/abs/2304.10244
    • Code: https://github.com/Francis0625/Omni-SR
    • Keywords: Lightweight
  8. CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large Input
    • Paper: https://arxiv.org/abs/2304.06454
    • Keywords: Large Input
  9. Image Super-Resolution Using T-Tetromino Pixels
    • Paper: https://arxiv.org/abs/2111.09013
  10. Spectral Bayesian Uncertainty for Image Super-resolution
    • Paper:
  11. Memory-friendly Scalable Super-resolution via Rewinding Lottery Ticket Hypothesis
    • Paper:
    • News: PAMI中心8项研究成果被计算机视觉顶级会议CVPR2023录用
    • Keywords: Lightweight

任意尺度超分

  1. Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution
    • Paper: https://arxiv.org/abs/2303.05156
    • Keywords: Arbitrary-Scale, Flow
  2. Super-Resolution Neural Operator
    • Paper: https://arxiv.org/abs/2303.02584
    • Code: https://github.com/2y7c3/Super-Resolution-Neural-Operator
    • Keywords: Arbitrary-Scale
  3. OPE-SR: Orthogonal Position Encoding for Designing a Parameter-free Upsampling Module in Arbitrary-scale Image Super-Resolution
    • Paper: https://arxiv.org/abs/2303.01091
    • Keywords: Arbitrary-scale
  4. Human Guided Ground-truth Generation for Realistic Image Super-resolution
    • Paper: https://arxiv.org/abs/2303.13069
    • Code: https://github.com/ChrisDud0257/HGGT
    • Keywords: RealSR
  5. Cascaded Local Implicit Transformer for Arbitrary-Scale Super-Resolution
    • Paper: https://arxiv.org/abs/2303.16513
    • Code: https://github.com/jaroslaw1007/CLIT
  6. Implicit Diffusion Models for Continuous Super-Resolution
    • Paper: https://arxiv.org/abs/2303.16491
    • Code: https://github.com/ree1s/idm
  7. CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolution
    • Paper: https://arxiv.org/abs/2212.04362
    • Code: https://github.com/caojiezhang/CiaoSR
    • Keywords: Attention, Implicit
  8. Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance Pursuit
    • Paper:
    • Code: https://github.com/neuralchen/EQSR

盲超分

  1. Better “CMOS” Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-Resolution
    • Paper: https://arxiv.org/abs/2304.03542
  2. Learning Generative Structure Prior for Blind Text Image Super-resolution
    • Paper: https://arxiv.org/abs/2303.14726
    • Code: https://github.com/csxmli2016/MARCONet

视频超分

  1. Learning Spatial-Temporal Implicit Neural Representations for Event-Guided Video Super-Resolution
    • Paper: https://arxiv.org/abs/2303.13767
    • Code: http://github.io/cvpr23/egvsr
    • Keywords: Implicit Neural Representations
  2. Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting
    • Paper: https://arxiv.org/abs/2303.08331
    • Code: https://github.com/coulsonlee/STDO-CVPR2023.git
  3. Consistent Direct Time-of-Flight Video Depth Super-Resolution
    • Paper: https://arxiv.org/abs/2211.08658
    • Keywords: dToF
  4. Compression-Aware Video Super-Resolution
    • Paper:
  5. Structured Sparsity Learning for Efficient Video Super-Resolution
    • Paper: https://arxiv.org/abs/2206.07687
    • Code: https://github.com/Zj-BinXia/SSL

特殊场景

  1. Denoising Diffusion Probabilistic Models for Robust Image Super-Resolution in the Wild
    • Paper: https://arxiv.org/abs/2302.07864
    • Keywords: Diffusion, Wild
  2. Learning to Zoom and Unzoom
    • Paper: https://arxiv.org/abs/2303.15390
    • Code: https://tchittesh.github.io/lzu/
    • Keywords: Image Resampling
  3. Toward Stable, Interpretable, and Lightweight Hyperspectral Super-resolution
    • Code: https://github.com/WenjinGuo/DAEM
    • Keywords: Hyperspectral
  4. OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer
    • Paper: https://arxiv.org/abs/2302.03453
    • Code: https://github.com/Fanghua-Yu/OSRT
    • Keywords: Omnidirectional Image
  5. Cross-Guided Optimization of Radiance Fields with Multi-View Image Super-Resolution for High-Resolution Novel View Synthesis
    • Paper:
  6. Guided Depth Super-Resolution by Deep Anisotropic Diffusion
    • Paper: https://arxiv.org/abs/2211.11592
    • Code: https://github.com/prs-eth/Diffusion-Super-Resolution
    • Keywords: Depth image, Diffusion
  7. CutMIB: Boosting Light Field Super-Resolution via Multi-View Image Blending
    • Paper:
    • Keywords: Light Field
    • Author: http://staff.ustc.edu.cn/~zwxiong/
  8. B-spline Texture Coefficients Estimator for Screen Content Image Super-Resolution
    • Paper: https://ipl.dgist.ac.kr/BTC_cvpr23.pdf
    • Code: https://github.com/ByeongHyunPak/btc
    • Keywords: Screen Content Image
  9. Spatial-Frequency Mutual Learning for Face Super-Resolution
    • Paper:
    • Keywords: Face
  10. Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-Resolution
    • Paper:
    • Keywords: Mobile Image
  11. Zero-Shot Dual-Lens Super-Resolution
    • Paper:
    • Code: https://github.com/XrKang/ZeDuSR
    • Keywords: Zero-Shot, Dual-Lens

总结

从本届接收的论文来看，超分方向上目前主要聚焦于任意尺度超分（ Arbitrary-Scale SR）。

参考资料

  1. CVPR2023最新信息及论文下载（Papers/Codes/Project/PaperReading／Demos/直播分享／论文分享会等）
  2. Awesome-Super-Resolution
  3. CVPR 2023 Accepted Papers
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