ICCV2021|底层视觉和图像生成相关论文汇总(如果觉得有帮助,欢迎点赞和收藏)
- 1.图像生成(Image Generation)
- Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts
- PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering
- Toward Spatially Unbiased Generative Models
- Disentangled Lifespan Face Synthesis
- Handwriting Transformers
- Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Translation
- ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement
- Paint Transformer: Feed Forward Neural Painting with Stroke Prediction
- GAN Inversion for Out-of-Range Images with Geometric Transformations
- The Animation Transformer: Visual Correspondence via Segment Matching
- Image Synthesis via Semantic Composition
- 2.图像编辑(Image Manipulation/Image Editing)
- EigenGAN: Layer-Wise Eigen-Learning for GANs
- From Continuity to Editability: Inverting GANs with Consecutive Images
- HeadGAN: One-shot Neural Head Synthesis and Editing
- Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation
- Sketch Your Own GAN
- A Latent Transformer for Disentangled Face Editing in Images and Videos
- Learning Facial Representations from the Cycle-consistency of Face
- StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery
- Talk-to-Edit: Fine-Grained Facial Editing via Dialog
- Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing
- 3.图像风格迁移(Image Transfer)
- 4.图像翻译(Image to Image Translation)
- 5.图像修复(Image Inpaiting/Image Completion)
- Implicit Internal Video Inpainting
- Internal Video Inpainting by Implicit Long-range Propagation
- Occlusion-Aware Video Object Inpainting
- High-Fidelity Pluralistic Image Completion with Transformers
- Image Inpainting via Conditional Texture and Structure Dual Generation
- CR-Fill: Generative Image Inpainting with Auxiliary Contextual Reconstruction
- 6.图像超分辨率(Image Super-Resolution)
- Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution
- Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
- Deep Blind Video Super-resolution
- Omniscient Video Super-Resolution
- Learning A Single Network for Scale-Arbitrary Super-Resolution
- Deep Reparametrization of Multi-Frame Super-Resolution and Denoising
- Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts
- Attention-Based Multi-Reference Learning for Image Super-Resolution
- 7.图像去雨(Image Deraining)
- 8.图像去雾(Image Dehazing)
- 9.去模糊(Deblurring)
- 10.去噪(Denoising)
- 11.图像恢复(Image Restoration)
- 12.图像增强(Image Enhancement)
- 13.图像质量评价(Image Quality Assessment)
- 14.插帧(Frame Interpolation)
- 15.视频/图像压缩(Video/Image Compression)
- 16.其他底层视觉任务(Other Low Level Vision)
- Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation
- Focal Frequency Loss for Image Reconstruction and Synthesis
- ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss
- IICNet: A Generic Framework for Reversible Image Conversion
- Self-Conditioned Probabilistic Learning of Video Rescaling
- HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset
- A New Journey from SDRTV to HDRTV
- SSH: A Self-Supervised Framework for Image Harmonization
- Towards Vivid and Diverse Image Colorization with Generative Color Prior
- Towards Flexible Blind JPEG Artifacts Removal
A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation
整理汇总下2021年ICCV中图像生成(Image Generation)和底层视觉(Low-Level Vision)任务相关的论文和代码,包括图像生成,图像编辑,图像风格迁移,图像翻译,图像修复,图像超分及其他底层视觉任务。大家如果觉得有帮助,欢迎点赞和收藏~~
优先在Github更新:Awesome-ICCV2021-Low-Level-Vision,欢迎star~
知乎:https://zhuanlan.zhihu.com/p/412822286
参考或转载请注明出处
ICCV2021官网:https://iccv2021.thecvf.com/
ICCV2021完整论文列表:https://openaccess.thecvf.com/ICCV2021
开会时间:2021年10月11日-10月17日
【Contents】
- 1.图像生成(Image Generation)
- 2.图像编辑(Image Manipulation/Image Editing)
- 3.图像风格迁移(Image Transfer)
- 4.图像翻译(Image to Image Translation)
- 5.图像修复(Image Inpaiting/Image Completion)
- 6.图像超分辨率(Image Super-Resolution)
- 7.图像去雨(Image Deraining)
- 8.图像去雾(Image Dehazing)
- 9.去模糊(Deblurring)
- 10.去噪(Denoising)
- 11.图像恢复(Image Restoration)
- 12.图像增强(Image Enhancement)
- 13.图像质量评价(Image Quality Assessment)
- 14.插帧(Frame Interpolation)
- 15.视频/图像压缩(Video/Image Compression)
- 16.其他底层视觉任务(Other Low Level Vision)
1.图像生成(Image Generation)
Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts
- Paper:https://arxiv.org/abs/2104.00887
- Code:https://github.com/clovaai/mxfont
- 小样本字体生成
PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering
- Code:https://github.com/RenYurui/PIRender
Toward Spatially Unbiased Generative Models
- Code:https://github.com/jychoi118/toward_spatial_unbiased
Disentangled Lifespan Face Synthesis
- Paper:https://arxiv.org/abs/2108.02874
- Code:https://github.com/clovaai/mxfont
Handwriting Transformers
- Paper:https://arxiv.org/abs/2104.03964
- Code:https://github.com/ankanbhunia/Handwriting-Transformers
Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Translation
- Paper:https://arxiv.org/abs/2103.16146
ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement
- Paper:https://arxiv.org/abs/2104.02699
- Code:https://github.com/yuval-alaluf/restyle-encoder
Paint Transformer: Feed Forward Neural Painting with Stroke Prediction
- Paper:https://arxiv.org/abs/2108.03798
- Code:https://github.com/huage001/painttransformer
GAN Inversion for Out-of-Range Images with Geometric Transformations
- Paper:https://arxiv.org/abs/2108.08998
The Animation Transformer: Visual Correspondence via Segment Matching
- Paper:https://arxiv.org/abs/2109.02614
- 手绘图变动画
Image Synthesis via Semantic Composition
- Paper:https://shepnerd.github.io/scg/resources/01145.pdf
- Code:https://github.com/dvlab-research/SCGAN
2.图像编辑(Image Manipulation/Image Editing)
EigenGAN: Layer-Wise Eigen-Learning for GANs
- Paper:https://arxiv.org/abs/2104.12476
- Code:https://github.com/LynnHo/EigenGAN-Tensorflow
From Continuity to Editability: Inverting GANs with Consecutive Images
- Paper:https://arxiv.org/abs/2107.13812
- Code:https://github.com/cnnlstm/InvertingGANs_with_ConsecutiveImgs
HeadGAN: One-shot Neural Head Synthesis and Editing
- Paper:https://arxiv.org/abs/2012.08261
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation
- Code:https://github.com/csyxwei/OroJaR
Sketch Your Own GAN
- Paper:https://arxiv.org/abs/2108.02774
- Code:https://github.com/PeterWang512/GANSketching
A Latent Transformer for Disentangled Face Editing in Images and Videos
- Paper:https://arxiv.org/abs/2106.11895
- Code:https://github.com/InterDigitalInc/Latent-Transformer
Learning Facial Representations from the Cycle-consistency of Face
- Paper:https://arxiv.org/abs/2108.03427
- Code:https://github.com/jiarenchang/facecycle
StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery
- Paper:https://arxiv.org/abs/2103.17249
- Code:https://github.com/orpatashnik/StyleCLIP
Talk-to-Edit: Fine-Grained Facial Editing via Dialog
- Paper:https://arxiv.org/abs/2109.04425
- Code:https://github.com/yumingj/Talk-to-Edit
Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing
- Paper:https://cuiaiyu.github.io/dressing-in-order/Cui_Dressing_in_Order.pdf
- Code:https://github.com/cuiaiyu/dressing-in-order
3.图像风格迁移(Image Transfer)
ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity
- Paper:https://arxiv.org/abs/2103.09776
Domain Aware Universal Style Transfer
- Paper:https://arxiv.org/abs/2108.04441
- Code:https://github.com/Kibeom-Hong/Domain-Aware-Style-Transfer
AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer
- Paper:https://arxiv.org/abs/2108.03647
- Code:https://github.com/Huage001/AdaAttN
4.图像翻译(Image to Image Translation)
SPatchGAN: A Statistical Feature Based Discriminator for Unsupervised Image-to-Image Translation
- Paper:https://arxiv.org/abs/2103.16219
- Code:https://github.com/NetEase-GameAI/SPatchGAN
Scaling-up Disentanglement for Image Translation
- Paper:https://arxiv.org/abs/2103.14017
- Code:https://github.com/avivga/overlord
5.图像修复(Image Inpaiting/Image Completion)
Implicit Internal Video Inpainting
- Code:https://github.com/Tengfei-Wang/Implicit-Internal-Video-Inpainting
Internal Video Inpainting by Implicit Long-range Propagation
- Code:https://github.com/Tengfei-Wang/Annotated-4K-Videos
Occlusion-Aware Video Object Inpainting
- Paper:https://arxiv.org/abs/2108.06765
High-Fidelity Pluralistic Image Completion with Transformers
- Paper:https://arxiv.org/abs/2103.14031
- Code:https://github.com/raywzy/ICT
Image Inpainting via Conditional Texture and Structure Dual Generation
- Paper:https://arxiv.org/abs/2108.09760v1
- Code:https://github.com/Xiefan-Guo/CTSDG
CR-Fill: Generative Image Inpainting with Auxiliary Contextual Reconstruction
- Paper:https://arxiv.org/abs/2011.12836
- Code:https://github.com/zengxianyu/crfill
6.图像超分辨率(Image Super-Resolution)
Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution
- Code:https://github.com/JingyunLiang/MANet
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
- Code:https://github.com/JingyunLiang/HCFlow
Deep Blind Video Super-resolution
- Code:https://github.com/csbhr/Deep-Blind-VSR
Omniscient Video Super-Resolution
- Code:https://github.com/psychopa4/OVSR
Learning A Single Network for Scale-Arbitrary Super-Resolution
- Paper:https://arxiv.org/abs/2004.03791
- Code:https://github.com/LongguangWang/ArbSR
Deep Reparametrization of Multi-Frame Super-Resolution and Denoising
- Paper:https://arxiv.org/abs/2108.08286
Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts
- Paper:https://arxiv.org/abs/2104.06191
Attention-Based Multi-Reference Learning for Image Super-Resolution
- Paper:https://openaccess.thecvf.com/content/ICCV2021/papers/Pesavento_Attention-Based_Multi-Reference_Learning_for_Image_Super-Resolution_ICCV_2021_paper.pdf
7.图像去雨(Image Deraining)
Structure-Preserving Deraining with Residue Channel Prior Guidance
- Code:https://github.com/Joyies/SPDNet
8.图像去雾(Image Dehazing)
9.去模糊(Deblurring)
Bringing Events into Video Deblurring with Non consecutively Blurry Frames
- Code:https://github.com/shangwei5/D2Net
Rethinking Coarse-to-Fine Approach in Single Image Deblurring
- Paper:https://arxiv.org/abs/2108.05054
- Code:https://github.com/chosj95/MIMO-UNet
Bringing Events into Video Deblurring with Non consecutively Blurry Frames
- Code:https://github.com/shangwei5/D2Net
10.去噪(Denoising)
C2N: Practical Generative Noise Modeling for Real-World Denoising
- Paper:https://openaccess.thecvf.com/content/ICCV2021/papers/Jang_C2N_Practical_Generative_Noise_Modeling_for_Real-World_Denoising_ICCV_2021_paper.pdf
11.图像恢复(Image Restoration)
Spatially-Adaptive Image Restoration using Distortion-Guided Networks
- Paper:https://arxiv.org/abs/2108.08617
Dynamic Attentive Graph Learning for Image Restoration
- Paper:https://arxiv.org/abs/2109.06620
- Code:https://github.com/jianzhangcs/DAGL
12.图像增强(Image Enhancement)
StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement
- Paper:https://arxiv.org/abs/2107.12898
- Code:https://github.com/IDKiro/StarEnhancer
Real-time Image Enhancer via Learnable Spatial-aware 3D Lookup Tables
- Paper:https://arxiv.org/abs/2108.08697
13.图像质量评价(Image Quality Assessment)
MUSIQ: Multi-scale Image Quality Transformer
- Paper:https://arxiv.org/abs/2108.05997
14.插帧(Frame Interpolation)
XVFI: eXtreme Video Frame Interpolation
- Paper:https://arxiv.org/abs/2103.16206
- Code:https://github.com/JihyongOh/XVFI
Asymmetric Bilateral Motion Estimation for Video Frame Interpolation
- Paper: https://arxiv.org/abs/2108.06815
- Code: https://github.com/JunHeum/ABME
15.视频/图像压缩(Video/Image Compression)
Extending Neural P-frame Codecs for B-frame Coding
- Paper:https://arxiv.org/abs/2104.00531
Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform
- Paper:https://arxiv.org/abs/2108.09551
- Code:https://github.com/micmic123/QmapCompression
16.其他底层视觉任务(Other Low Level Vision)
Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation
- Code:https://github.com/Anonymous-iccv2021-paper3163/CaFM-Pytorch
- 视频传输
Focal Frequency Loss for Image Reconstruction and Synthesis
- Paper:https://arxiv.org/abs/2012.12821
- Code:https://github.com/EndlessSora/focal-frequency-loss
- 频域损失,补充空域损失的不足
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss
- Code:https://github.com/weitingchen83/ICCV2021-Single-Image-Desnowing-HDCWNet
IICNet: A Generic Framework for Reversible Image Conversion
- Code:https://github.com/felixcheng97/IICNet
Self-Conditioned Probabilistic Learning of Video Rescaling
- Paper:https://arxiv.org/abs/2107.11639
HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset
- Paper:https://arxiv.org/abs/2103.14943
- Code:https://github.com/guanyingc/DeepHDRVideo
A New Journey from SDRTV to HDRTV
- Paper:https://arxiv.org/abs/2108.07978
- Code:https://github.com/chxy95/HDRTVNet
SSH: A Self-Supervised Framework for Image Harmonization
- Paper:https://arxiv.org/abs/2108.06805
- Code:https://github.com/VITA-Group/SSHarmonization
Towards Vivid and Diverse Image Colorization with Generative Color Prior
- Paper:https://arxiv.org/abs/2108.08826
Towards Flexible Blind JPEG Artifacts Removal
- Paper:https://github.com/jiaxi-jiang/FBCNN/releases/download/v1.0/FBCNN_ICCV2021.pdf
- Code:https://github.com/jiaxi-jiang/FBCNN