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Image Generation

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하위 태스크: 23
평가표: 93
보존된 평가 기록: 870

Image Generation (synthesis) is the task of generating new images from an existing dataset.

Unconditional generation refers to generating samples unconditionally from the dataset, i.e. $p(y)$
Conditional image generation (subtask) refers to generating samples conditionally from the dataset, based on a label, i.e. $p(y|x)$.

In this section, you can find state-of-the-art leaderboards for unconditional generation. For conditional generation, and other types of image generations, refer to the subtasks.

<span style="color:grey; opacity: 0.6">( Image credit: StyleGAN )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/HUST-SLOW/SeaS

공식 코드

SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning

https://github.com/HYOJINPARK/MC_GAN

공식 코드

MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis

https://github.com/Ha0Tang/AsymmetricGAN

공식 코드

Asymmetric GANs for Image-to-Image Translation

https://github.com/Ha0Tang/AttentionGAN

공식 코드

Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation

https://github.com/Ha0Tang/BiGraphGAN

공식 코드

Bipartite Graph Reasoning GANs for Person Image Generation

https://github.com/Ha0Tang/C2GAN

공식 코드

Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes

https://github.com/Ha0Tang/DAGAN

공식 코드

Dual Attention GANs for Semantic Image Synthesis

https://github.com/Ha0Tang/EdgeGAN

공식 코드

Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis

https://github.com/Ha0Tang/GestureGAN

공식 코드

Unified Generative Adversarial Networks for Controllable Image-to-Image Translation

https://github.com/Ha0Tang/LGGAN

공식 코드

Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation

https://github.com/Ha0Tang/SelectionGAN

공식 코드

Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation

https://github.com/Ha0Tang/XingGAN

공식 코드

XingGAN for Person Image Generation

https://github.com/Hammour-steak/GOUB

공식 코드

Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge

https://github.com/Hamsterrrrrrrrr/multiscale-ssh

공식 코드

Multi-scale decomposition of sea surface height snapshots using machine learning

https://github.com/Hangz-nju-cuhk/Talking-Face_PC-AVS

공식 코드

Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation

https://github.com/Harry-Thasarathan/TCVC

공식 코드

Automatic Temporally Coherent Video Colorization

https://github.com/Healthcare-Robotics/BodyPressure

공식 코드

BodyPressure -- Inferring Body Pose and Contact Pressure from a Depth Image

https://github.com/Healthcare-Robotics/bodies-at-rest

공식 코드

Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data

https://github.com/HelenMao/MSGAN

공식 코드

Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis

https://github.com/HelenMao/SAVI2I

공식 코드

Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors

https://github.com/HideUnderBush/UI2I_via_StyleGAN2

공식 코드

Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network

https://github.com/HieuPhan33/MaskGAN

공식 코드

Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation

https://github.com/HighwayWu/ImageInpainting

공식 코드

Deep Generative Model for Image Inpainting with Local Binary Pattern Learning and Spatial Attention

https://github.com/HighwayWu/InpaintingForensics

공식 코드

GIID-Net: Generalizable Image Inpainting Detection via Neural Architecture Search and Attention

https://github.com/Hindawi91/Pseudo_Supervised_Metrics

공식 코드

Domain-knowledge Inspired Pseudo Supervision (DIPS) for Unsupervised Image-to-Image Translation Models to Support Cross-Domain Classification

https://github.com/HoinJung/Unified-Debiaisng-VLM-SFID

공식 코드

A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks

https://github.com/Holliemin9090/Mammographic-mass-CAD-via-pseudo-color-mammogram-and-Mask-R-CNN

공식 코드

Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN

https://github.com/Holmeswww/PPOGAN

공식 코드

Improving GAN Training with Probability Ratio Clipping and Sample Reweighting

https://github.com/Honlan/DMT

공식 코드

Disentangled Makeup Transfer with Generative Adversarial Network

https://github.com/Hosein47/IEA-GAN

공식 코드

PE-GAN: Prior Embedding GAN for PXD images at Belle II

https://github.com/HsinYingLee/DRIT

공식 코드

Diverse Image-to-Image Translation via Disentangled Representations

https://github.com/HuangZhiChao95/FewShotMotionTransfer

공식 코드

Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling

https://github.com/HuiSiqi/Auxiliary-Loss-Reweighting-for-Image-Inpainting

공식 코드

Auxiliary Loss Reweighting for Image Inpainting

https://github.com/HydroML/X0isAllYouNeed

공식 코드

Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots

https://github.com/Hyun1A/GLoCE

공식 코드

Localized Concept Erasure for Text-to-Image Diffusion Models Using Training-Free Gated Low-Rank Adaptation

https://github.com/Hzzone/MTLFace

공식 코드

When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework

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