https://github.com/mahmed10/camss
공식 코드CAM-Seg: A Continuous-valued Embedding Approach for Semantic Image Generation
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/mahmoudnafifi/HistoGAN
공식 코드HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms
https://github.com/mahmoudnafifi/WB_color_augmenter
공식 코드https://github.com/maifoundations/indexmark
공식 코드Training-Free Watermarking for Autoregressive Image Generation
https://github.com/majedelhelou/BIGPrior
공식 코드BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration
https://github.com/majedelhelou/fc-diffusion
공식 코드Fuzzy-Conditioned Diffusion and Diffusion Projection Attention Applied to Facial Image Correction
https://github.com/majid-daliri/kdeformer
공식 코드KDEformer: Accelerating Transformers via Kernel Density Estimation
https://github.com/malldimi1/keypointstolandmarks
공식 코드https://github.com/mamadou-keita/vlm-detect
공식 코드Bi-LORA: A Vision-Language Approach for Synthetic Image Detection
https://github.com/mandt-lab/PSLD
공식 코드https://github.com/manem-lab/lung-ddpm
공식 코드Lung-DDPM: Semantic Layout-guided Diffusion Models for Thoracic CT Image Synthesis
https://github.com/manjaryp/ganvsgraphicsvsreal
공식 코드Distinguishing Natural and Computer-Generated Images using Multi-Colorspace fused EfficientNet
https://github.com/manugar/imagestyletransfer
공식 코드https://github.com/maorong-wang/esrm
공식 코드Dealing with Synthetic Data Contamination in Online Continual Learning
https://github.com/maplebb/controlthinker
공식 코드https://github.com/mapooon/face2diffusion
공식 코드https://github.com/maps-research/gemrec
공식 코드https://github.com/marcdemers/FIGR-8
공식 코드https://github.com/marcoamonteiro/pi-GAN
공식 코드pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis
https://github.com/marcoaversa/diffinfinite
공식 코드DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology
https://github.com/mariiadrozdova/diffusion-for-sources-characterisation
공식 코드Radio-astronomical Image Reconstruction with Conditional Denoising Diffusion Model
https://github.com/marinadominguez/diffusion-for-us-images
공식 코드Diffusion as Sound Propagation: Physics-inspired Model for Ultrasound Image Generation
https://github.com/mark-yu1/interactive-image-inpainting
공식 코드https://github.com/markweberdev/maskbit
공식 코드https://github.com/markxcloud/cspd
공식 코드Continuous Speculative Decoding for Autoregressive Image Generation
https://github.com/marsggbo/EAGAN
공식 코드EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs
https://github.com/martaskrt/fkc-diffusion
공식 코드Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
https://github.com/martenlienen/bsi
공식 코드https://github.com/marwankefah/SISSI
공식 코드Seamless Iterative Semi-Supervised Correction of Imperfect Labels in Microscopy Images
https://github.com/masa-ue/svdd
공식 코드Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding
https://github.com/masaaki-75/meditok
공식 코드MedITok: A Unified Tokenizer for Medical Image Synthesis and Interpretation
https://github.com/mashathepotato/GSoC-Quantum-Diffusion-Model
공식 코드https://github.com/matansel/pix2vertex
공식 코드Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation
https://github.com/matejgrcic/DenseFlow
공식 코드https://github.com/mateuszpoleski/geoguide
공식 코드https://github.com/matrix-alpha/matrix-alpha.github.io
공식 코드Accountable Textual-Visual Chat Learns to Reject Human Instructions in Image Re-creation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.