Delta Denoising Score
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Cited by 77 in Diffusion models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
We introduce Delta Denoising Score (DDS), a novel scoring function for text-based image editing that guides minimal modifications of an input image towards the content described in a target prompt. DDS leverages the rich generative prior of text-to-image diffusion models and can be used as a loss term in an optimization problem to steer an image towards a desired direction dictated by a text. DDS utilizes the Score Distillation Sampling (SDS) mechanism for the purpose of image editing. We show that using only SDS often produces non-detailed and blurry outputs due to noisy gradients. To address this issue, DDS uses a prompt that matches the input image to identify and remove undesired erroneous directions of SDS. Our key premise is that SDS should be zero when calculated on pairs of matched prompts and images, meaning that if the score is non-zero, its gradients can be attributed to the erroneous component of SDS. Our analysis demonstrates the competence of DDS for text based image-to-image translation. We further show that DDS can be used to train an effective zero-shot image translation model. Experimental results indicate that DDS outperforms existing methods in terms of stability and quality, highlighting its potential for real-world applications in text-based image editing.
Key facts. Cited by 120 papers in the map (data through 7 Oct 2026). Builds on 39 of its 48 references that are in the map. First posted on arXiv 14 Apr 2023.
Builds on
39 of 48 references.
References · 39
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
- 2020Denoising Diffusion Implicit Modelscited by 9,655
- 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
- 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
- 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
- 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
- 2022Classifier-Free Diffusion Guidancecited by 5,717
- 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
27 more
- 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
- 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
- 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
- 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
- 2021Image Super-Resolution via Iterative Refinementcited by 1,506
- 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,172
- 2022Null-text Inversion for Editing Real Images using Guided Diffusion Modelscited by 1,168
- 2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 990
- 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924
- 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 921
- 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translationcited by 897
- 2016COCO-Stuff: Thing and Stuff Classes in Contextcited by 858
- 2022DiffEdit: Diffusion-based semantic image editing with mask guidancecited by 643
- 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
- 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
- 2023Zero-shot Image-to-Image Translationcited by 503
- 2022Blended Latent Diffusioncited by 430
- 2022MotionCLIP: Exposing Human Motion Generation to CLIP Spacecited by 406
- 2022Text2LIVE: Text-Driven Layered Image and Video Editingcited by 312
- 2022VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidancecited by 285
- 2023P+: Extended Textual Conditioning in Text-to-Image Generationcited by 242
- 2023DreamBooth3D: Subject-Driven Text-to-3D Generationcited by 235
- 2021CLIPstyler: Image Style Transfer with a Single Text Conditioncited by 203
- 2022Sketch-Guided Text-to-Image Diffusion Modelscited by 180
- 2021Layered Neural Atlases for Consistent Video Editingcited by 137
- 2022Diffusion Guided Domain Adaptation of Image Generatorscited by 35
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Citing papers per year: 2023: 23; 2024: 48; 2025: 32; 2026: 17.
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