Rebalancing Reference Frame Dominance to Improve Motion in Image-to-Video Models

arXiv:2605.19398 · cs.CV, cs.AI · Submitted 2026-05-19 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-05-19

Updated: 2026-09-25

Code: https://github.com/black-forest-labs/flux

Terminology

• Fidelity — 20× in this paper · explained in 2 episodes
• Diffusion Model — 12× in this paper · explained in 8 episodes
• Diffusion Models — 11× in this paper · explained in 6 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Benchmark — 8× in this paper · explained in 2 episodes
• Consistency — 7× in this paper · explained in 3 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Model-Agnostic — 6× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• PE Video Dataset — 3× in this paper
• Ablation study — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Optical Flow — 2× in this paper · explained in 2 episodes
• Rectified Flow — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Distillation — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Variational Autoencoder (VAE) — 1× in this paper · explained in 3 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
• HunyuanVideo 1.5 Technical Report
• Wan: Open and Advanced Large-Scale Video Generative Models
• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• Open-Sora Plan: Open-Source Large Video Generation Model
• Imagen Video: High Definition Video Generation with Diffusion Models
• LTX-Video: Realtime Video Latent Diffusion
• MAGI-1: Autoregressive Video Generation at Scale
• I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models
• FlashI2V: Fourier-Guided Latent Shifting Prevents Conditional Image Leakage in Image-to-Video Generation
• Improving Motion in Image-to-Video Models via Adaptive Low-Pass Guidance
• Auto-Encoding Variational Bayes
• Classifier-Free Diffusion Guidance
• MotionCFG: Boosting Motion Dynamics via Stochastic Concept Perturbation
• Memory-V2V: Memory-Augmented Video-to-Video Diffusion for Consistent Multi-Turn Editing
• Universal Image Immunization against Diffusion-based Image Editing via Semantic Injection

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