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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/sanofi-public/miphei-vit

공식 코드

MIPHEI-ViT: Multiplex Immunofluorescence Prediction from H&E Images using ViT Foundation Models

https://github.com/sanoscience/simuscope

공식 코드

SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Models

https://github.com/sapphire497/style-transformer

공식 코드

Style Transformer for Image Inversion and Editing

https://github.com/sarmadfismael/lrm_i2i

공식 코드

Unsupervised Domain Adaptation for Semantic Segmentation using One-shot Image-to-Image Translation via Latent Representation Mixing

https://github.com/sbarratt/inception-score-pytorch

공식 코드

A New Formulation of Lipschitz Constrained With Functional Gradient Learning for GANs

https://github.com/sbyebss/monge_map_solver

공식 코드

Neural Monge Map estimation and its applications

https://github.com/sccsok/coprguard

공식 코드

Harnessing Frequency Spectrum Insights for Image Copyright Protection Against Diffusion Models

https://github.com/scechnicka/URCDM

공식 코드

URCDM: Ultra-Resolution Image Synthesis in Histopathology

https://github.com/schindlerepfl/thermo-nerf

공식 코드

ThermoNeRF: Joint RGB and Thermal Novel View Synthesis for Building Facades using Multimodal Neural Radiance Fields

https://github.com/schuture/benchmarking-awesome-diffusion-models

공식 코드

X-IQE: eXplainable Image Quality Evaluation for Text-to-Image Generation with Visual Large Language Models

https://github.com/scraed/CharacteristicGuidanceWebUI

공식 코드

Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale

https://github.com/scu-zjz/Mesorch

공식 코드

Mesoscopic Insights: Orchestrating Multi-scale & Hybrid Architecture for Image Manipulation Localization

https://github.com/scu-zjz/forensichub

공식 코드

ForensicHub: A Unified Benchmark & Codebase for All-Domain Fake Image Detection and Localization

https://github.com/scu-zjz/imdlbenco

공식 코드

IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localization

https://github.com/scu-zjz/sparsevit

공식 코드

Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding Transformer

https://github.com/scuwyh2000/diff-ii

공식 코드

Inversion Circle Interpolation: Diffusion-based Image Augmentation for Data-scarce Classification

https://github.com/scxue/DM-NonUniform

공식 코드

Accelerating Diffusion Sampling with Optimized Time Steps

https://github.com/scxue/SA-Solver

공식 코드

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models

https://github.com/sczzz3/ehrdiff

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EHRDiff: Exploring Realistic EHR Synthesis with Diffusion Models

https://github.com/seacrowd/seacrowd.github.io

공식 코드

Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia

https://github.com/seanjia/srunit

공식 코드

Semantically Robust Unpaired Image Translation for Data with Unmatched Semantics Statistics

https://github.com/searecluse/cvprw2024

공식 코드

A visualization method for data domain changes in CNN networks and the optimization method for selecting thresholds in classification tasks

https://github.com/seasonSH/LiftedGAN

공식 코드

Lifting 2D StyleGAN for 3D-Aware Face Generation

https://github.com/seasonSH/SemanticStyleGAN

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SemanticStyleGAN: Learning Compositional Generative Priors for Controllable Image Synthesis and Editing

https://github.com/seasonSH/WarpGAN

공식 코드

WarpGAN: Automatic Caricature Generation

https://github.com/seermer/RTGen

공식 코드

RTGen: Generating Region-Text Pairs for Open-Vocabulary Object Detection

https://github.com/segmind/distill-sd

공식 코드

BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion

https://github.com/sehwankimstat/ebgan

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A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules

https://github.com/seilna/CNN-Units-in-NLP

공식 코드

Discovery of Natural Language Concepts in Individual Units of CNNs

https://github.com/self-distilled-stylegan/self-distilled-internet-photos

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Self-Distilled StyleGAN: Towards Generation from Internet Photos

https://github.com/semchan/HyperLips

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HyperLips: Hyper Control Lips with High Resolution Decoder for Talking Face Generation

https://github.com/sen-mao/3di2i-translation

공식 코드

3D-Aware Multi-Class Image-to-Image Translation with NeRFs

https://github.com/sen-mao/StyleDiffusion

공식 코드

StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing

https://github.com/sengopal/cv-activity-classification

공식 코드

Multi class activity classification in videos using Motion History Image generation

https://github.com/senmaoy/RAT-Diffusion

공식 코드

Data Extrapolation for Text-to-image Generation on Small Datasets

https://github.com/senmaoy/recurrent-affine-transformation-for-text-to-image-synthesis

공식 코드

Recurrent Affine Transformation for Text-to-image Synthesis

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.