https://github.com/researchmm/AOT-GAN-for-Inpainting
공식 코드Aggregated Contextual Transformations for High-Resolution Image Inpainting
Papers with Code 아카이브
Image Generation
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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/researchmm/PEN-Net-for-Inpainting
공식 코드Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting
https://github.com/researchmm/TTSR
공식 코드Learning Texture Transformer Network for Image Super-Resolution
https://github.com/researchmm/ai_illustrator
공식 코드AI Illustrator: Translating Raw Descriptions into Images by Prompt-based Cross-Modal Generation
https://github.com/researchmm/generate-it
공식 코드Unifying Multimodal Transformer for Bi-directional Image and Text Generation
https://github.com/retinal-research/cunsb-rfie
공식 코드CUNSB-RFIE: Context-aware Unpaired Neural Schr"{o}dinger Bridge in Retinal Fundus Image Enhancement
https://github.com/retinal-research/ote-gan
공식 코드Optimal Transport Guided Unsupervised Learning for Enhancing low-quality Retinal Images
https://github.com/retinal-research/redot
공식 코드https://github.com/reubendo/mhvae
공식 코드Unified Cross-Modal Image Synthesis with Hierarchical Mixture of Product-of-Experts
https://github.com/revisitq/Pseudo-Stereo-3D
공식 코드Pseudo-Stereo for Monocular 3D Object Detection in Autonomous Driving
https://github.com/reyllama/mixdl
공식 코드Few-shot Image Generation with Mixup-based Distance Learning
https://github.com/rezashkv/diffusion_pruning
공식 코드Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models
https://github.com/rf5/simple-asgan
공식 코드https://github.com/rf5/transfusion-asr
공식 코드https://github.com/rhgao/on-demand-learning
공식 코드https://github.com/richardobi/ccnet
공식 코드Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models
https://github.com/richardobi/frd-score
공식 코드Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets
https://github.com/richardobi/medigan
공식 코드medigan: a Python library of pretrained generative models for medical image synthesis
https://github.com/richardqiyi/projectedex
공식 코드ProjectedEx: Enhancing Generation in Explainable AI for Prostate Cancer
https://github.com/richardwth/MMD-GAN
공식 코드https://github.com/ridgerchu/TCJA
공식 코드TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks
https://github.com/riiid/ppap
공식 코드https://github.com/rinongal/StyleGAN-nada
공식 코드StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
https://github.com/rinongal/textual_inversion
공식 코드An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
https://github.com/riolys/disdiff
공식 코드Disrupting Diffusion: Token-Level Attention Erasure Attack against Diffusion-based Customization
https://github.com/rishidarkdevil/daam-i2i
공식 코드https://github.com/rizavelioglu/tryoffdiff
공식 코드TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models
https://github.com/rmokady/structural-analogy
공식 코드https://github.com/rmpku/cpdm
공식 코드A Dataset and Benchmark for Copyright Infringement Unlearning from Text-to-Image Diffusion Models
https://github.com/robert-graf/readable-conditional-denoising-diffusion
공식 코드Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
https://github.com/robin-wzq/cclap
공식 코드CCLAP: Controllable Chinese Landscape Painting Generation via Latent Diffusion Model
https://github.com/robincourant/DIRECTOR
공식 코드E.T. the Exceptional Trajectories: Text-to-camera-trajectory generation with character awareness
https://github.com/roblox/smoothcache
공식 코드SmoothCache: A Universal Inference Acceleration Technique for Diffusion Transformers
https://github.com/roboflow/rf100-vl
공식 코드Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models
https://github.com/rocavincent/iguane_harmonization
공식 코드IGUANe: a 3D generalizable CycleGAN for multicenter harmonization of brain MR images
https://github.com/rocketappslab/SCA-GAN
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.