風(fēng)格遷移
1. PairedCycleGAN: Asymmetric Style Transfer for Applying and Removing Makeup
（給人臉化妝的風(fēng)格轉(zhuǎn)移）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Chang_PairedCycleGAN_Asymmetric_Style_CVPR_2018_paper.pdf
2.CartoonGAN: Generative Adversarial Networks for Photo Cartoonization
（將圖片轉(zhuǎn)化為卡通風(fēng)格的GAN）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_CartoonGAN_Generative_Adversarial_CVPR_2018_paper.pdf
3.StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
（人臉多種風(fēng)格轉(zhuǎn)換）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_StarGAN_Unified_Generative_CVPR_2018_paper.pdf
4.Multi-Content GAN for Few-Shot Font Style Transfer
（字體風(fēng)格轉(zhuǎn)換）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Azadi_Multi-Content_GAN_for_CVPR_2018_paper.pdf
5.DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks
（圖到圖轉(zhuǎn)換）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Ma_DA-GAN_Instance-Level_Image_CVPR_2018_paper.pdf
6. Conditional Image-to-Image translation
（圖到圖的轉(zhuǎn)換）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Conditional_Image-to-Image_Translation_CVPR_2018_paper.pdf
圖片處理
1. DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
（去模糊）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Kupyn_DeblurGAN_Blind_Motion_CVPR_2018_paper.pdf
2.Attentive Generative Adversarial Network for Raindrop Removal from A Single Image
（去除圖片中的雨滴）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Qian_Attentive_Generative_Adversarial_CVPR_2018_paper.pdf
3. Deep Photo Enhancer: Unpaired Learning for Image Enhancement from Photographs with GANs
（用于照片增強(qiáng)）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Deep_Photo_Enhancer_CVPR_2018_paper.pdf
4. SeGAN: Segmenting and Generating the Invisible
（去遮擋）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_SeGAN_Segmenting_and_CVPR_2018_paper.pdf
5.Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal
（去陰影）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Stacked_Conditional_Generative_CVPR_2018_paper.pdf
6.Image Blind Denoising With Generative Adversarial Network Based Noise Modeling
（去噪聲）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Image_Blind_Denoising_CVPR_2018_paper.pdf
7. Single Image Dehazing via Conditional Generative Adversarial Network
（去噪聲）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Single_Image_Dehazing_CVPR_2018_paper.pdf
圖片生成
1. ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing
（空間轉(zhuǎn)換生成圖片）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_ST-GAN_Spatial_Transformer_CVPR_2018_paper.pdf
2. SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis
（由邊框生成圖片）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_SketchyGAN_Towards_Diverse_CVPR_2018_paper.pdf
3. TextureGAN: Controlling Deep Image Synthesis with Texture Patches
（由紋路生成圖片）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Xian_TextureGAN_Controlling_Deep_CVPR_2018_paper.pdf
4. Eye In-Painting with Exemplar Generative Adversarial Networks
（給人物畫(huà)眼睛）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Dolhansky_Eye_In-Painting_With_CVPR_2018_paper.pdf
5.Photographic Text-to-Image Synthesis with a Hierarchically-nested Adversarial Network
（文本生成圖片）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Photographic_Text-to-Image_Synthesis_CVPR_2018_paper.pdf
6. Logo Synthesis and Manipulation with Clustered Generative Adversarial Networks
（生成logo）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Sage_Logo_Synthesis_and_CVPR_2018_paper.pdf
7. Cross-View Image Synthesis Using Conditional GANs
（街區(qū)俯視圖和直視轉(zhuǎn)換）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Regmi_Cross-View_Image_Synthesis_CVPR_2018_paper.pdf
8. AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
（文本生成圖片）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_AttnGAN_Fine-Grained_Text_CVPR_2018_paper.pdf
9. High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
（圖像高分辨率）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_High-Resolution_Image_Synthesis_CVPR_2018_paper.pdf
人臉相關(guān)
1. Finding Tiny Faces in the Wild with Generative Adversarial Network
（對(duì)低分辨率的人臉檢測(cè)）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Bai_Finding_Tiny_Faces_CVPR_2018_paper.pdf
2. Learning Face Age Progression: A Pyramid Architecture of GANs
（預(yù)測(cè)年齡）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Learning_Face_Age_CVPR_2018_paper.pdf
3. Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs
（對(duì)低分辨率人臉超分辨率）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Bulat_Super-FAN_Integrated_Facial_CVPR_2018_paper.pdf
4. Towards Open-Set Identity Preserving Face Synthesis
（人臉合成）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Bao_Towards_Open-Set_Identity_CVPR_2018_paper.pdf
5. Weakly Supervised Facial Action Unit Recognition through Adversarial Training
（人臉表情識(shí)別）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Peng_Weakly_Supervised_Facial_CVPR_2018_paper.pdf
6.FaceID-GAN: Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis
（生成多角度人臉）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_FaceID-GAN_Learning_a_CVPR_2018_paper.pdf
7. UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognition
（人臉生成）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Deng_UV-GAN_Adversarial_Facial_CVPR_2018_paper.pdf
8.Face Aging with Identity-Preserved Conditional Generative Adversarial Networks
（人臉老化）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Face_Aging_With_CVPR_2018_paper.pdf
人體相關(guān)
1. Deformable GANs for Pose-based Human Image Generation
（人物姿態(tài)遷移）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Siarohin_Deformable_GANs_for_CVPR_2018_paper.pdf
2. Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
(用GAN生成人行為軌跡追蹤)
http://openaccess.thecvf.com/content_cvpr_2018/papers/Gupta_Social_GAN_Socially_CVPR_2018_paper.pdf
3. GANerated Hands for Real-Time 3D Hand Tracking from Monocular RGB
（用GAN生成的手勢(shì)圖片做手勢(shì)追蹤的數(shù)據(jù)集）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Mueller_GANerated_Hands_for_CVPR_2018_paper.pdf
4. Multistage Adversarial Losses for Pose-Based Human Image Synthesis
（人體姿態(tài)合成）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Si_Multistage_Adversarial_Losses_CVPR_2018_paper.pdf
5. Disentangled Person Image Generation
（人體合成）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Ma_Disentangled_Person_Image_CVPR_2018_paper.pdf
domain adaptation
（這個(gè)沒(méi)來(lái)得及找了，可能轉(zhuǎn)行咯~ 唉）
1. Generate to Adapt: Aligning Domains Using Generative Adversarial Networks
2. Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation
3. Adversarial Feature Augmentation for Unsupervised Domain Adaptation
4. Domain Generalization With Adversarial Feature Learning
5. Image to Image Translation for Domain Adaptation
6. Duplex Generative Adversarial Network for Unsupervised Domain Adaptation
7. Conditional Generative Adversarial Network for Structured Domain Adaptation
目標(biāo)跟蹤檢測(cè)
1.Generative Adversarial Learning Towards Fast Weakly Supervised Detection
（弱監(jiān)督檢測(cè)）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Generative_Adversarial_Learning_CVPR_2018_paper.pdf
2. SINT++: Robust Visual Tracking via Adversarial Positive Instance Generation
（對(duì)抗學(xué)習(xí)生成軌跡樣本）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_SINT_Robust_Visual_CVPR_2018_paper.pdf
3. VITAL: VIsual Tracking via Adversarial Learning
http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_VITAL_VIsual_Tracking_CVPR_2018_paper.pdf
GAN模型優(yōu)化
1. SGAN: An Alternative Training of Generative Adversarial Network
（替代訓(xùn)練GAN）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Chavdarova_SGAN_An_Alternative_CVPR_2018_paper.pdf
2. GAGAN: Geometry-Aware Generative Adversarial Networks
（一種關(guān)注幾何外形的GAN）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Kossaifi_GAGAN_Geometry-Aware_Generative_CVPR_2018_paper.pdf
3.Global versus Localized Generative Adversarial Nets
(局部?jī)?yōu)化GAN)
http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Global_Versus_Localized_CVPR_2018_paper.pdf
4. Generative Adversarial Image Synthesis with Decision Tree Latent Controller
（決策樹(shù)）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Kaneko_Generative_Adversarial_Image_CVPR_2018_paper.pdf
5. Unsupervised Deep Generative Adversarial Hashing Network
（哈希GAN）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Dizaji_Unsupervised_Deep_Generative_CVPR_2018_paper.pdf
6. Multi-Agent Diverse Generative Adversarial Networks
（多個(gè)生成器GAN）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Ghosh_Multi-Agent_Diverse_Generative_CVPR_2018_paper.pdf
7. Duplex Generative Adversarial Network for Unsupervised Domain Adaptation
（雙鑒別器GAN）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Duplex_Generative_Adversarial_CVPR_2018_paper.pdf
圖像分割
1. Translating and Segmenting Multimodal Medical Volumes With Cycle- and Shape-Consistency Generative Adversarial Network
（圖像分割）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Translating_and_Segmenting_CVPR_2018_paper.pdf
行人重識(shí)別
1. Person Transfer GAN to Bridge Domain Gap for Person Re-Identification
（用GAN生成的人體檢測(cè)的圖片）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Wei_Person_Transfer_GAN_CVPR_2018_paper.pdf
2. Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification
http://openaccess.thecvf.com/content_cvpr_2018/papers/Deng_Image-Image_Domain_Adaptation_CVPR_2018_paper.pdf
視覺(jué)特征提取
1. Visual Feature Attribution using Wasserstein GANs
http://openaccess.thecvf.com/content_cvpr_2018/papers/Baumgartner_Visual_Feature_Attribution_CVPR_2018_paper.pdf
域自適應(yīng)學(xué)習(xí)
1. Generate To Adapt: Aligning Domains using Generative Adversarial Networks
（視覺(jué)域自適應(yīng)）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Generate_to_Adapt_CVPR_2018_paper.pdf
圖像檢索
1. HashGAN: Deep Learning to Hash with Pair Conditional Wasserstein GAN
http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_HashGAN_Deep_Learning_CVPR_2018_paper.pdf
遷移學(xué)習(xí)
1.Partial Transfer Learning With Selective Adversarial Networks
http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Partial_Transfer_Learning_CVPR_2018_paper.pdf
視頻生成
1. MoCoGAN: Decomposing Motion and Content for Video Generation
（用GAN生成視頻）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulyakov_MoCoGAN_Decomposing_Motion_CVPR_2018_paper.pdf
2. Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks
（生成延時(shí)視頻）
http://openaccess.thecvf.com/content_cvpr_2018/papers/Xiong_Learning_to_Generate_CVPR_2018_paper.pdf
小結(jié)：
可以看出GAN相關(guān)的論文還不少呀，各個(gè)方面的都有，可是我個(gè)人覺(jué)得，可能沒(méi)有那種特別厲害的吧~hh
--------------------- 本文來(lái)自 眉間細(xì)雪 的CSDN 博客 ，全文地址請(qǐng)點(diǎn)擊：https://blog.csdn.net/weixin_42445501/article/details/82792311?utm_source=copy