Diffusion Editing with Soft Mask: Pixel Level Redo of Image and Video with Adjustable Strength

arXiv:2610.00359 · cs.GR, cs.AI, cs.CV, cs.MM · Submitted 2026-09-30 · Read on arXiv

cs.GR, cs.AI, cs.CV, cs.MM

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Diffusion Model — 25× in this paper · explained in 8 episodes
• Diffusion Models — 21× in this paper · explained in 6 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Rectified Flow — 6× in this paper · explained in 3 episodes
• Unified Redo — 6× in this paper
• Generative Modeling — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Diffusion-Damped Langevin — 4× in this paper
• Langevin Dynamics — 4× in this paper · explained in 2 episodes
• Differential Diffusion — 3× in this paper
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Computer Vision and Pattern Recognition — 2× in this paper
• Flow Matching — 2× in this paper · explained in 8 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Inverse Problem — 2× in this paper · explained in 2 episodes
• Model-Agnostic — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Deep Unsupervised Learning using Nonequilibrium Thermodynamics
• Score-Based Generative Modeling through Stochastic Differential Equations
• Denoising Diffusion Probabilistic Models
• Elucidating the Design Space of Diffusion-Based Generative Models
• DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models
• UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models
• Flow Matching for Generative Modeling
• Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
• FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space
• Qwen-Image Technical Report
• TD-Paint: Faster Diffusion Inpainting Through Time Aware Pixel Conditioning
• Classifier-Free Diffusion Guidance
• CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
• Wan: Open and Advanced Large-Scale Video Generative Models
• Denoising Diffusion Implicit Models
• IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
• Emu Edit: Precise Image Editing via Recognition and Generation Tasks
• Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
• Diffusion Posterior Sampling for General Noisy Inverse Problems
• Diffusion Models Beat GANs on Image Synthesis

Related papers

• SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-Based Humanoid Control
• CADReasoner: Iterative Program Editing for CAD Reverse Engineering
• QuadLink: Autoregressive Quad-Dominant Mesh Generation via Point-Relation Learning
• DrawVideo: Grounded and Faithful Multi-Shot Video Generation from Storyboard Keyframe Sketches
• MotionPersona: Real-Time Locomotion Control across Personas, Bodies, and Styles
• MeshSplatBench: A Unified Benchmark for Triangle- and Mesh-Based Neural Rendering