ICCV 2023

官網(wǎng)鏈接：https://iccv2023.thecvf.com/
會(huì)議時(shí)間：2023 年 10 月 2 日至 6 日，法國巴黎（Paris）。
ICCV 2023統(tǒng)計(jì)數(shù)據(jù)：收錄 2160 篇。

現(xiàn)將超分辨率方向上接收的論文匯總?cè)缦?，遺漏之處還請大家斧正。

圖像超分

1. SRFormer: Permuted Self-Attention for Single Image Super-Resolution
   • Paper: http://arxiv.org/abs/2303.09735
   • Keywords: Transformer
   • Blog: ICCV 2023 | 南開程明明團(tuán)隊(duì)提出新穎注意力機(jī)制用于圖像超分辨率任務(wù)
2. Dual Aggregation Transformer for Image Super-Resolution
   • Paper: https://arxiv.org/abs/2308.03364
   • Code: https://github.com/zhengchen1999/DAT
   • Keywords: Transformer
   • Video: ICCV 2023【已開源】| 上交大與蘇黎世聯(lián)邦理工學(xué)院領(lǐng)銜發(fā)布，即插即用雙向聚合Transformer
   • Blog: ICCV 2023 | 利用雙重聚合的Transformer進(jìn)行圖像超分辨率
3. Feature Modulation Transformer: Cross-Refinement of Global Representation via High-Frequency Prior for Image Super-Resolution
   • Paper: http://arxiv.org/abs/2308.05022
   • Code: https://github.com/AVC2-UESTC/CRAFT-SR.git
   • Keywords: Transformer
4. MSRA-SR: Image Super-resolution Transformer with Multi-scale Shared Representation Acquisition
   • Paper: ICCV 2023 Open Access Repository
   • Code:
   • Keywords: Transformer
5. Content-Aware Local GAN for Photo-Realistic Super-Resolution
   • Paper: ICCV 2023 Open Access Repository
   • Code: https://github.com/jkpark0825/CAL
   • Keywords: GAN

輕量化超分

1. Lightweight Image Super-Resolution with Superpixel Token Interaction
   • Paper: ICCV 2023 Open Access Repository
   • Code: https://github.com/ArcticHare105/SPIN
   • Keywords: Lightweight
2. Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution
   • Paper: ICCV 2023 Open Access Repository
   • Code: https://github.com/Jiamian-Wang/Iterative-Soft-Shrinkage-SR
   • Keywords: Efficient
3. Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-Resolution
   • Paper: https://arxiv.org/abs/2307.08544
   • Code: https://github.com/liuguandu/RC-LUT
   • Keywords: Efficient
4. Boosting Single Image Super-Resolution via Partial Channel Shifting
   • Paper: ICCV 2023 Open Access Repository
   • Code: https://github.com/OwXiaoM/PCS
   • Keywords: Efficient
5. Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution
   • Paper: https://arxiv.org/abs/2302.13800
   • Code: https://github.com/sunny2109/SAFMN
   • Keywords: Efficient
   • Blog: 五分鐘論文速讀 | Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution
6. DLGSANet: Lightweight Dynamic Local and Global Self-Attention Networks for Image Super-Resolution
   • Paper: https://arxiv.org/abs/2301.02031
   • Code: https://neonleexiang.github.io/DLGSANet/
   • Keywords: Lightweight
   • Blog: 五分鐘論文速讀 | DLGSANet: Lightweight Dynamic Local and Global Self-Attention Networks for Image SR

盲超分

1. MetaF2N: Blind Image Super-Resolution by Learning Efficient Model Adaptation from Faces
   • Paper: https://arxiv.org/abs/2309.08113
   • Code: https://github.com/yinzhicun/MetaF2N
   • Keywords: Faces
2. Learning Correction Filter via Degradation-Adaptive Regression for Blind Single Image Super-Resolution
   • Paper: ICCV 2023 Open Access Repository
   • Code: https://github.com/edbca/DARSR
   • Keywords: Blind

Burst SR

1. Self-Supervised Burst Super-Resolution
   • Paper: ICCV 2023 Open Access Repository
   • Code:
   • Keywords: Self-Supervised
2. Towards Real-World Burst Image Super-Resolution: Benchmark and Method
   • Paper: ICCV 2023 Open Access Repository
   • Code: https://github.com/yjsunnn/FBANet
   • Keywords: Dataset

Reference-Based

1. LMR: A Large-Scale Multi-Reference Dataset for Reference-Based Super-Resolution
   • Paper: https://arxiv.org/abs/2303.04970添加鏈接描述
   • Code:
   • Keywords: Reference-Based

特殊場景

1. A Benchmark for Chinese-English Scene Text Image Super-Resolution
   • Paper: http://arxiv.org/abs/2308.03262
   • Code: https://github.com/mjq11302010044/Real-CE
   • Keywords: Scene text image super-resolution (STISR), dataset
2. Learning Non-Local Spatial-Angular Correlation for Light Field Image Super-Resolution
   • Paper: https://arxiv.org/abs/2302.08058
   • Code: https://github.com/ZhengyuLiang24/EPIT
   • Keywords: Light Field
3. Spherical Space Feature Decomposition for Guided Depth Map Super-Resolution
   • Paper: https://arxiv.org/abs/2303.08942
   • Code: https://github.com/Zhaozixiang1228/GDSR-SSDNet
   • Keywords: Depth Map

遙感

1. HSR-Diff: Hyperspectral Image Super-Resolution via Conditional Diffusion Models
   • Paper: ICCV 2023 Open Access Repository
   • Keywords: Hyperspectral, diffusion
2. ESSAformer: Efficient Transformer for Hyperspectral Image Super-resolution
   • Paper: https://arxiv.org/abs/2307.14010
   • Code: https://github.com/Rexzhan/ESSAformer
   • Keywords: Efficient, Transformer

醫(yī)學(xué)

1. Rethinking Multi-Contrast MRI Super-Resolution: Rectangle-Window Cross-Attention Transformer and Arbitrary-Scale Upsampling
   • Paper: ICCV 2023 Open Access Repository
   • Keywords: MRI, arbitrary-scale
2. Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and Reconstruction
   • Paper: ICCV 2023 Open Access Repository
   • Code: https://github.com/lpcccc-cv/MC-VarNet
   • Keywords: MRI
3. CuNeRF: Cube-Based Neural Radiance Field for Zero-Shot Medical Image Arbitrary-Scale Super Resolution
   • Paper: https://arxiv.org/abs/2303.16242
   • Code: https://github.com/NarcissusEx/CuNeRF
   • Keywords: Arbitrary-Scale

視頻超分

1. MoTIF: Learning Motion Trajectories with Local Implicit Neural Functions for Continuous Space-Time Video Super-Resolution
   • Paper: https://arxiv.org/abs/2307.07988
   • Code: https://github.com/sichun233746/MoTIF
   • Keywords: Continuous Space-Time
2. Learning Data-Driven Vector-Quantized Degradation Model for Animation Video Super-Resolution
   • Paper: https://arxiv.org/abs/2303.09826
   • Code: https://github.com/researchmm/VQD-SR
   • Keywords: Real-world
3. Multi-Frequency Representation Enhancement with Privilege Information for Video Super-Resolution
   • Paper: ICCV 2023 Open Access Repository
   • Code:
   • Keywords: Video

總結(jié)

1. SISR 領(lǐng)域中，接收的文章大部分都基于Transformer結(jié)構(gòu)，展現(xiàn)出蹭熱點(diǎn)的重要性。
2. 接收文章中提出了多個(gè)新數(shù)據(jù)集，集中在某些特殊場景（如burst，Scene text，Reference-Based等），有利于SR領(lǐng)域的進(jìn)一步發(fā)展，也挖下了坑。
3. 輕量化超分文章比例大，展現(xiàn)出更偏實(shí)用化的研究趨勢，在醫(yī)學(xué)和高光譜等領(lǐng)域也涌現(xiàn)了相關(guān)研究。

參考資料

1. ICCV 2023 papers
2. ICCV 2023 超分辨率（Super-Resolution）論文匯總