Consistent-Inversion introduces reverse consistency guidance that corrects early target denoising steps by checking reversibility toward the source inversion trajectory under the original prompt.
Dragdiffusion: Harnessing diffusion models for interactive point-based image editing.arXiv preprint arXiv:2306.14435,
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
years
2026 4roles
method 1polarities
use method 1representative citing papers
Training-free motion conditioning for latent video diffusion by direct injection of low-frequency phase from a reference video into the diffusion noise.
A study deriving mathematical formulations and bounds for diffusion editing objectives while empirically comparing methods on fidelity and control metrics and discussing ethical issues.
citing papers explorer
-
Consistent-Inversion: Reverse Consistency Guidance for Structure-Preserving Visual Editing
Consistent-Inversion introduces reverse consistency guidance that corrects early target denoising steps by checking reversibility toward the source inversion trajectory under the original prompt.
-
{\Phi}-Noise: Training-Free Temporal Video Conditioning via Phase-Based Noise Manipulation
Training-free motion conditioning for latent video diffusion by direct injection of low-frequency phase from a reference video into the diffusion noise.
-
On the Controllability-Fidelity Frontier in Diffusion Editing
A study deriving mathematical formulations and bounds for diffusion editing objectives while empirically comparing methods on fidelity and control metrics and discussing ethical issues.
- PhyEdit: Towards Real-World Object Manipulation via Physically-Grounded Image Editing