Borrowing from anything: A generalizable framework for reference-guided instance editing

arXiv:2512.15138 · cs.CV · Submitted 2025-12-17 · Read on arXiv

cs.CV

Submitted: 2025-12-17

Updated: 2026-09-27

Code: https://github.com/Xiao0219/GENIE

Terminology

• Alignment — 10× in this paper · explained in 1 episode
• Fidelity — 8× in this paper · explained in 2 episodes
• Adaptive Residual Scaling Module — 7× in this paper
• Diffusion Model — 7× in this paper · explained in 8 episodes
• Spatial Alignment Module — 7× in this paper
• Entanglement — 6× in this paper · explained in 3 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Consistency — 5× in this paper · explained in 3 episodes
• Diffusion Models — 5× in this paper · explained in 6 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Computer Vision and Pattern Recognition — 4× in this paper
• Core — 4× in this paper · explained in 2 episodes
• Progressive Attention Fusion — 4× in this paper
• Robustness — 3× in this paper · explained in 5 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 2× in this paper
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes

Sources

• Insert Anything: Image Insertion via In-Context Editing in DiT
• Paste, Inpaint and Harmonize via Denoising: Subject-Driven Image Editing with Pre-Trained Diffusion Model
• ObjectStitch: Generative Object Compositing
• CompleteMe: Reference-based Human Image Completion
• FreeEdit: Mask-free Reference-based Image Editing with Multi-modal Instruction
• Improving Diffusion Models for Authentic Virtual Try-on in the Wild
• EfficientMT: Efficient Temporal Adaptation for Motion Transfer in Text-to-Video Diffusion Models
• IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
• SmartControl: Enhancing ControlNet for Handling Rough Visual Conditions
• Adam: A Method for Stochastic Optimization
• DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

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