CVPR 2023 | 最全 AIGC 论文清单汇总版，30个方向130篇！

一、图像转换/翻译

1、Masked and Adaptive Transformer for Exemplar Based Image Translation
2、LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data
3、Interactive Cartoonization with Controllable Perceptual Factors
4、LightPainter: Interactive Portrait Relighting with Freehand Scribble
5、Picture that Sketch: Photorealistic Image Generation from Abstract Sketches
6、Few-shot Semantic Image Synthesis with Class Affinity Transfer

二、GAN改进

7、CoralStyleCLIP: Co-optimized Region and Layer Selection for Image Editing
8、Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models
9、Efficient Scale-Invariant Generator with Column-Row Entangled Pixel Synthesis
10、Fix the Noise: Disentangling Source Feature for Transfer Learning of StyleGAN
11、Improving GAN Training via Feature Space Shrinkage
12、Look ATME: The Discriminator Mean Entropy Needs Attention
13、NoisyTwins: Class-Consistent and Diverse Image Generation through StyleGANs
14、DeltaEdit: Exploring Text-free Training for Text-Driven Image Manipulation
15、Delving StyleGAN Inversion for Image Editing: A Foundation Latent Space Viewpoint
16、SIEDOB: Semantic Image Editing by Disentangling Object and Background

三、可控文生图/定制化文生图

17、DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
18、Ablating Concepts in Text-to-Image Diffusion Models
19、Multi-Concept Customization of Text-to-Image Diffusion
20、Imagic: Text-Based Real Image Editing with Diffusion Models
21、Shifted Diffusion for Text-to-image Generation
22、SpaText: Spatio-Textual Representation for Controllable Image Generation
23、Scaling up GANs for Text-to-Image Synthesis
24、GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis
25、Variational Distribution Learning for Unsupervised Text-to-Image Generation

四、图像恢复

26、Bitstream-Corrupted JPEG Images are Restorable: Two-stage Compensation and Alignment Framework for Image Restoration
27、Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bank
28、Efficient and Explicit Modelling of Image Hierarchies for Image Restoration
29、Generating Aligned Pseudo-Supervision from Non-Aligned Data forImage Restoration in Under-Display Camera
30、 Learning Semantic-Aware Knowledge Guidance for Low-Light Image Enhancement
31、Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Model
32、Robust Model-based Face Reconstruction through Weakly-Supervised Outlier Segmentation
33、Robust Unsupervised StyleGAN Image Restoration

五、布局可控生成

34、LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation
35、LayoutDM: Discrete Diffusion Model for Controllable Layout Generation
36、PosterLayout: A New Benchmark and Approach for Content-aware Visual-Textual Presentation Layout
37、Unifying Layout Generation with a Decoupled Diffusion Model
38、Unsupervised Domain Adaption with Pixel-level Discriminator for Image-aware Layout Generation

六、医学图像

39、High-resolution image reconstruction with latent diffusion models from human brain activity
40、 Leveraging GANs for data scarcity of COVID-19: Beyond the hype
41、Why is the winner the best?
45、Solving 3D Inverse Problems using Pre-trained 2D Diffusion Models

七、人脸相关

46、A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images
47、DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration
48、DiffusionRig: Learning Personalized Priors for Facial Appearance Editing
49、Fine-Grained Face Swapping via Regional GAN Inversion
50、SunStage: Portrait Reconstruction and Relighting using the Sun as a Light Stage

八、3D相关

51、3DQD: Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process
52、Controllable Mesh Generation Through Sparse Latent Point Diffusion Models
53、GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds
54、GINA-3D: Learning to Generate Implicit Neural Assets in the Wild
55、Graphics Capsule: Learning Hierarchical 3D Face Representations from 2D Images
56、HOLODIFFUSION: Training a 3D Diffusion Model using 2D Images
57、Learning 3D-aware Image Synthesis with Unknown Pose Distribution
58、Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field
59、Magic3D: High-Resolution Text-to-3D Content Creation
60、NeuFace: Realistic 3D Neural Face Rendering from Multi-view Images
61、NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models
62、Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars
63、SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation
64、SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation
65、Solving 3D Inverse Problems using Pre-trained 2D Diffusion Models
66、T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
67、TAPS3D: Text-Guided 3D Textured Shape Generation from Pseudo Supervision

九、deepfake检测

68、Detecting and Grounding Multi-Modal Media Manipulation

十、图像超分

69、Activating More Pixels in Image Super-Resolution Transformer
70、Denoising Diffusion Probabilistic Models for Robust Image Super-Resolution in the Wild
71、Implicit Diffusion Models for Continuous Super-Resolution
72、Perception-Oriented Single Image Super-Resolution using Optimal Objective Estimation
73、Structured Sparsity Learning for Efficient Video Super-Resolution
74、Super-Resolution Neural Operator
75、Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting

十一、风格迁移

76、CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer
77、Inversion-Based Style Transfer with Diffusion Models
78、Neural Preset for Color Style Transfer

十二、去雨去噪去模糊

79、Learning A Sparse Transformer Network for Effective Image Deraining
80、Masked Image Training for Generalizable Deep Image Denoising
81、Uncertainty-Aware Unsupervised Image Deblurring with Deep Residual Prior

十三、图像分割

82、DiGA: Distil to Generalize and then Adapt for Domain Adaptive Semantic Segmentation
83、Generative Semantic Segmentation
84、Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs
85、Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models

十四、视频相关

86、A Dynamic Multi-Scale Voxel Flow Network for Video Prediction
87、A Unified Pyramid Recurrent Network for Video Frame Interpolation
88、Conditional Image-to-Video Generation with Latent Flow Diffusion Models
89、Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding
90、Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation
91、MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation
92、MOSO: Decomposing MOtion, Scene and Object for Video Prediction
93、Text-Visual Prompting for Efficient 2D Temporal Video Grounding
94、Towards End-to-End Generative Modeling of Long Videos with Memory-Efficient Bidirectional Transformers
95、Video Probabilistic Diffusion Models in Projected Latent Space
96、VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

十五、对抗攻击

97、Adversarial Attack with Raindrops
98、TrojDiff: Trojan Attacks on Diffusion Models with Diverse Targets

十六、扩散模型改进

99、All are Worth Words: A ViT Backbone for Diffusion Models
100、Towards Practical Plug-and-Play Diffusion Models
101、Wavelet Diffusion Models are fast and scalable Image Generators

十七、数据增广

102、DCFace: Synthetic Face Generation with Dual Condition Diffusion Model
103、Leveraging GANs for data scarcity of COVID-19: Beyond the hype
104、Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field

十八、说话人生成

105、MetaPortrait: Identity-Preserving Talking Head Generation with Fast Personalized Adaptation
106、Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert

十九、视图合成

107、Consistent View Synthesis with Pose-Guided Diffusion Models

二十、目标检测

108、Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen Domains

二十一、人像生成-姿态迁移

109、Person Image Synthesis via Denoising Diffusion Model
110、VGFlow: Visibility guided Flow Network for Human Reposing

二十二、发型迁移

111、StyleGAN Salon: Multi-View Latent Optimization for Pose-Invariant Hairstyle Transfer

二十三、图像修复

112、SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model

二十四、表征学习

113、GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds

二十五、语音相关

114、Conditional Generation of Audio from Video via Foley Analogies
115、Physics-Driven Diffusion Models for Impact Sound Synthesis from Videos
116、Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment

二十六、域适应-迁移学习

117、Back to the Source: Diffusion-Driven Test-Time Adaptation
118、Domain Expansion of Image Generators
119、Zero-shot Generative Model Adaptation via Image-specific Prompt Learning

二十七、知识蒸馏

120、KD-DLGAN: Data Limited Image Generation via Knowledge Distillation

二十八、字体生成

121、CF-Font: Content Fusion for Few-shot Font Generation
122、Handwritten Text Generation from Visual Archetypes

二十九、异常检测

123、SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection

三十、数据集

124、An Image Quality Assessment Dataset for Portraits
125、CelebV-Text: A Large-Scale Facial Text-Video Dataset
126、Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenes
127、Uncurated Image-Text Datasets: Shedding Light on Demographic Bias

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原文链接： https://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA==&mid=2247500553&idx=1&sn=d878ff781f4aafd84a7c8284bfd2e664&chksm=fe2a61b2c95de8a4de30949bb42ddb12988123bc813798560a3f005b936263de83fddd40f4fa&scene=126&sessionid=0 CAP-VSTNet是 2023 年提出的风格迁移网络，它在处理风格迁移时表现出了优秀的性能。这个网络包括一个新的可逆残差网络和一个无偏线性变换模块，用于多功能风格转移。CAP-VSTNet的主要目标是解决内容相似度损失（包括特征和像素相似度）问题，这是导致逼真和视频风格迁移中出现伪影的主要问题。根据相关研究，CAP-VSTNet在多功能风格转移上表现出了有效性，并且可以产生较好的定性和定量结果。这意味着CAP-VSTNet能够在保留内容相似性的同时，实现高质量的风格迁移。 80、半监督学习、弱监督学习/无监督学习/自监督学习。36、行为识别/动作识别/检测/分割/定位。46、场景重建/视图合成/新视角合成。74、迁移学习/domain/自适应。23、图像复原/图像增强/图像重建。26、图像去噪/去模糊/去雨去雾。32、人脸生成/合成/重建/编辑。35、图像&视频检索/视频理解。41、GAN/生成式/对抗式。68、小样本学习/零样本学习。40、文本检测/识别/理解。17、视频生成/视频合成。27、图像编辑/图像修复。31、人脸识别/检测。42、图像生成/图像合成。 01图像分割类[1]AutoFocusFormer: Image Segmentation off the Grid推荐理由：该论文提出了 AutoFocusFormer (AFF)，一种局部注意力变换器图像识别主干，它通过学习保留任务最重要的像素来执行自适应下采样。放弃了经典的网格结构，该论文开发了一种新的基于点的局部注意力块，由平衡聚类模块和可学习的邻域合并模块提供便利，可以为最先进的分割头的... 它首先开发了一个上下文增强集体规范化(CEGN)层,通过将基于稀疏样本特征的统计数据替换为全局上下文特征的统计数据,然后设计了一种适配多层掩盖策略,以产生不同的高度,在不同大小的前景覆盖范围内产生最优遮瑕率。结果是一个基于素描的图像检测框架。作者：Lingchen Meng,Xiyang Dai,Yinpeng Chen,Pengchuan Zhang,Dongdong Chen,Mengchen Liu,Jianfeng Wang,Zuxuan Wu,Lu Yuan,Yu-Gang Jiang。整理：AI算法与图像处理 CVPR2023 论文和代码整理：https://github.com/DWCTOD/ CVPR2023 -Papers-with-Code-Demo欢迎关注公众号 AI算法与图像处理，获取更多干货：大家好,最近正在优化每周分享的 CVPR 论文 , 目前考虑按照不同类别去分类,方便不同方向的小伙伴挑选自己感兴趣的论文哈大家好，目前给每天的论文汇总接入chatGPT帮忙总结，目前在... 根据官方信息统计，今年共收到 9155 份提交，比去年增加了 12%，创下新纪录，今年接收了 2360 篇论文，接收率为 25.78%。作为对比，去年有 8100 多篇有效投稿，大会接收了 2067 篇，接收率为 25%。https:// cvpr2023 .thecvf.com/Conferences/ 2023 /AcceptedPapers推荐阅读西电IEEE Fellow团队出品！最新《Trans... 整理：AI算法与图像处理 CVPR2023 论文和代码整理：https://github.com/DWCTOD/ CVPR2023 -Papers-with-Code-Demo欢迎关注公众号 AI算法与图像处理，获取更多干货：大家好,最近正在优化每周分享的 CVPR 论文 , 目前考虑按照不同类别去分类,方便不同方向的小伙伴挑选自己感兴趣的论文哈大家好，目前给每天的论文汇总接入chatGPT帮忙总结，目前在... 编辑：桃子好困来源：新智元【导读】 CVPR 2023 有哪些亮点？从录用论文中我们又能看到CV领域有哪些趋势？一年一度的 CVPR 即将在6月18-22日加拿大温哥华正式开幕。每年，来自世界各地的成千上万的CV研究人员和工程师聚集在一起参加顶会。这个久负盛名的会议可以追溯到1983年，它代表了计算机视觉发展的巅峰。目前， CVPR 的h5指数所有会议或出版物中位列第四，仅次于《自然》、《科学》和... CVPR 2023 顶会论文接收结果出炉啦！ CVPR 2023 主委会官方发布这次论文接收数据：有效投稿 9155 篇（比 CVPR 2022 增加12%），收录 2360 篇，接收率为25.78 %。我整理了 CVPR 2023 的论文 &代码，分享给大家~持续更新中…扫码添加我领取资料此外，还有AAAI 2023 的论文 &代码，分享给大家~收持续更新中…扫码添加我领取资料最后，我...