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/aashish2000/anchor
공식 코드ANCHOR: LLM-driven News Subject Conditioning for Text-to-Image Synthesis
https://github.com/aashish2000/anna
공식 코드ANNA: Abstractive Text-to-Image Synthesis with Filtered News Captions
https://github.com/aayushbansal/PixelNN-Code
공식 코드https://github.com/abenhamadou/graph-self-supervised-learning-for-endoscopic-image-matching
공식 코드Graph Self-Supervised Learning for Endoscopic Image Matching
https://github.com/abhinavdhall/deepfake
공식 코드Not made for each other- Audio-Visual Dissonance-based Deepfake Detection and Localization
https://github.com/abhishektandon/bspline-fc
공식 코드https://github.com/aboriginer/hfs-sde
공식 코드https://github.com/abstractteen/gan_ownership_verification
공식 코드What can Discriminator do? Towards Box-free Ownership Verification of Generative Adversarial Network
https://github.com/abyildirim/inst-inpaint
공식 코드Inst-Inpaint: Instructing to Remove Objects with Diffusion Models
https://github.com/acecreamu/ssim-pan
공식 코드https://github.com/acharkq/next-mol
공식 코드NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
https://github.com/achernarwang/LiVO
공식 코드Embedding an Ethical Mind: Aligning Text-to-Image Synthesis via Lightweight Value Optimization
https://github.com/ada-cheng/cat-pruning
공식 코드CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion Models
https://github.com/adaptive-intelligent-robotics/MOUR-QD
공식 코드Multi-Objective Quality-Diversity in Unstructured and Unbounded Spaces
https://github.com/ader47/jittor-jieke-semantic_images_synthesis
공식 코드IIDM: Image-to-Image Diffusion Model for Semantic Image Synthesis
https://github.com/adjidieng/PresGANs
공식 코드https://github.com/adlnlp/attention_vl
공식 코드https://github.com/adobe-research/domain-expansion
공식 코드HyperGAN-CLIP: A Unified Framework for Domain Adaptation, Image Synthesis and Manipulation
https://github.com/adobe/antialiased-cnns
공식 코드https://github.com/adreamwu/ptq4dit
공식 코드PTQ4DiT: Post-training Quantization for Diffusion Transformers
https://github.com/adrian-baule/jumpAI
공식 코드https://github.com/advaitkumar3107/rsinet
공식 코드RSINet: Inpainting Remotely Sensed Images Using Triple GAN Framework
https://github.com/adwardlee/t2i_safety
공식 코드T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation
https://github.com/adymaharana/StoryViz
공식 코드Improving Generation and Evaluation of Visual Stories via Semantic Consistency
https://github.com/adymaharana/storydalle
공식 코드StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation
https://github.com/adymaharana/vlcstorygan
공식 코드Integrating Visuospatial, Linguistic and Commonsense Structure into Story Visualization
https://github.com/aei13/des
공식 코드Distorting Embedding Space for Safety: A Defense Mechanism for Adversarially Robust Diffusion Models
https://github.com/afeng-x/pixwizard
공식 코드PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions
https://github.com/affromero/SMILE
공식 코드SMILE: Semantically-guided Multi-attribute Image and Layout Editing
https://github.com/afm215/FaVGen
공식 코드Fairer Analysis and Demographically Balanced Face Generation for Fairer Face Verification
https://github.com/afruehstueck/insetGAN
공식 코드https://github.com/agis85/anatomy_modality_decomposition
공식 코드Disentangled Representation Learning in Cardiac Image Analysis
https://github.com/agonzgarc/cross-domain-disen
공식 코드https://github.com/ahmadmughees/layermix
공식 코드LayerMix: Enhanced Data Augmentation through Fractal Integration for Robust Deep Learning
https://github.com/ai-forever/Kandinsky-2
공식 코드Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.