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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/Bill2462/prompt-map

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PromptMap: An Alternative Interaction Style for AI-Based Image Generation

https://github.com/Boehringer-Ingelheim/stain-transfer

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A comparative evaluation of image-to-image translation methods for stain transfer in histopathology

https://github.com/BonnBytes/PyTorch-FWD

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Fréchet Wavelet Distance: A Domain-Agnostic Metric for Image Generation

https://github.com/Boyiliee/MoEx

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On Feature Normalization and Data Augmentation

https://github.com/Boyiliee/SITT

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SITTA: Single Image Texture Translation for Data Augmentation

https://github.com/BradSegal/CXR_PGGAN

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Evaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANs

https://github.com/Brian-Moser/zido

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Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution

https://github.com/BruceResearch/mFI-PSO

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mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks

https://github.com/ByteFlow-AI/TokenFlow

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TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

https://github.com/CHAITron/sketchdeco-code

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SketchDeco: Decorating B&W Sketches with Colour

https://github.com/CIFASIS/splitting_gan

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Class-Splitting Generative Adversarial Networks

https://github.com/CSAILVision/gandissect

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GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

https://github.com/CSU-JPG/TextAtlas

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TextAtlas5M: A Large-scale Dataset for Dense Text Image Generation

https://github.com/CUG-BEODL/MS2TAN

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Multi-scale Restoration of Missing Data in Optical Time-series Images with Masked Spatial-Temporal Attention Network

https://github.com/CV-IP/uqvi

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Uncertainty Quantification using Variational Inference for Biomedical Image Segmentation

https://github.com/CV-Lehigh/Bias_IMD

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Exploring Saliency Bias in Manipulation Detection

https://github.com/CXH-Research/IRFormer

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Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model

https://github.com/Cardio-AI/detcyclegan_pytorch

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Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation

https://github.com/Cardio-AI/memorization-ldm

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Unconditional Latent Diffusion Models Memorize Patient Imaging Data: Implications for Openly Sharing Synthetic Data

https://github.com/Carlyx/DPE

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DPE: Disentanglement of Pose and Expression for General Video Portrait Editing

https://github.com/Center-for-Health-Data-Science/scDGD

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The Deep Generative Decoder: MAP estimation of representations improves modeling of single-cell RNA data

https://github.com/Championchess/DLGAN

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DLGAN: Disentangling Label-Specific Fine-Grained Features for Image Manipulation

https://github.com/ChaoyueSong/X-DualNet

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Unsupervised 3D Pose Transfer with Cross Consistency and Dual Reconstruction

https://github.com/ChatHouseDiffusion/chathousediffusion

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ChatHouseDiffusion: Prompt-Guided Generation and Editing of Floor Plans

https://github.com/ChenHsing/Awesome-Video-Diffusion-Models

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A Survey on Video Diffusion Models

https://github.com/CherBass/ICAM

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ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping

https://github.com/CirclePassFilter/AS_GAN

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Adversarial symmetric GANs: bridging adversarial samples and adversarial networks

https://github.com/Cold-Winter/BachGAN

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BachGAN: High-Resolution Image Synthesis from Salient Object Layout

https://github.com/CompVis/net2net

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Network-to-Network Translation with Conditional Invertible Neural Networks

https://github.com/CompVis/taming-transformers

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Taming Transformers for High-Resolution Image Synthesis

https://github.com/CompVis/vunet

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A Variational U-Net for Conditional Appearance and Shape Generation

https://github.com/ControlNet/MARLIN

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MARLIN: Masked Autoencoder for facial video Representation LearnINg

https://github.com/Costwen/Ouroboros3D

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Ouroboros3D: Image-to-3D Generation via 3D-aware Recursive Diffusion

https://github.com/CreativePapers/Learn-to-Synthesize-and-Synthesize-to-Learn

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Learn to synthesize and synthesize to learn

https://github.com/CristianLazoQuispe/skin-lesion-segmentation-using-pix2pix

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Segmentation of skin lesions and their attributes using Generative Adversarial Networks

https://github.com/Cynetics/MSGNet

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Generating Annotated High-Fidelity Images Containing Multiple Coherent Objects

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