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/simontomaskarlsson/GAN-MRI
공식 코드https://github.com/simula/Kvasir-VQA
공식 코드https://github.com/simulamet-host/conditional-polyp-diffusion
공식 코드Mask-conditioned latent diffusion for generating gastrointestinal polyp images
https://github.com/sinaamirrajab/cardiacpathologysynthesis
공식 코드Pathology Synthesis of 3D-Consistent Cardiac MR Images using 2D VAEs and GANs
https://github.com/sincostanx/lusd
공식 코드LUSD: Localized Update Score Distillation for Text-Guided Image Editing
https://github.com/singhgautam/slate
공식 코드https://github.com/singlezombie/afldm
공식 코드Alias-Free Latent Diffusion Models:Improving Fractional Shift Equivariance of Diffusion Latent Space
https://github.com/sinhasam/crvae
공식 코드https://github.com/sinhayan/surfnet
공식 코드SurfNet: Generating 3D shape surfaces using deep residual networks
https://github.com/siqi0905/gardiff
공식 코드Improving Virtual Try-On with Garment-focused Diffusion Models
https://github.com/sisidai/InterFusion
공식 코드InterFusion: Text-Driven Generation of 3D Human-Object Interaction
https://github.com/sisl/EvidentialSparsification
공식 코드Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders
https://github.com/sixiaozheng/contextualstory
공식 코드ContextualStory: Consistent Visual Storytelling with Spatially-Enhanced and Storyline Context
https://github.com/siyuhuang/PoseStylizer
공식 코드Generating Person Images with Appearance-aware Pose Stylizer
https://github.com/siyuhuang/latent-space-anchoring
공식 코드Domain-Scalable Unpaired Image Translation via Latent Space Anchoring
https://github.com/sj-li/dp_gan
공식 코드Dual Pyramid Generative Adversarial Networks for Semantic Image Synthesis
https://github.com/sjtuplayer/anomalydiffusion
공식 코드AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model
https://github.com/sjtuzzw/complexity_control
공식 코드Complexity Control Facilitates Reasoning-Based Compositional Generalization in Transformers
https://github.com/skddj/loldu
공식 코드LoLDU: Low-Rank Adaptation via Lower-Diag-Upper Decomposition for Parameter-Efficient Fine-Tuning
https://github.com/skrmanne/3dlut_srgb_wb
공식 코드WB LUTs: Contrastive Learning for White Balancing Lookup Tables
https://github.com/skyworkai/mvgamba
공식 코드MVGamba: Unify 3D Content Generation as State Space Sequence Modeling
https://github.com/slark-prime/maai_optimizer
공식 코드https://github.com/sled-group/InfEdit
공식 코드https://github.com/sled-group/cyclenet
공식 코드CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation
https://github.com/sleighsoft/fti
공식 코드Improving the Evaluation of Generative Models with Fuzzy Logic
https://github.com/smatsumori/lattegan
공식 코드LatteGAN: Visually Guided Language Attention for Multi-Turn Text-Conditioned Image Manipulation
https://github.com/smerdov/CS_GO_Sensors_Data_Analysis
공식 코드AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors
https://github.com/smerdov/eSports_Sensors_Dataset
공식 코드https://github.com/smerdov/smart_chair_client
공식 코드https://github.com/smile365317/abp
공식 코드Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation
https://github.com/smileformylove/smartfreeedit
공식 코드SmartFreeEdit: Mask-Free Spatial-Aware Image Editing with Complex Instruction Understanding
https://github.com/smith42/synthetic-galaxy-distance
공식 코드Realistic galaxy image simulation via score-based generative models
https://github.com/smrhadou/robustunrolling
공식 코드https://github.com/smrhadou/unrolledglow
공식 코드https://github.com/snailforce/sim-net
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.