MirrorWorld: Taming Video Diffusion Models for Mirror Reflection Generation

arXiv:2608.07463 · cs.CV, cs.LG · Submitted 2026-08-07 · Read on arXiv

Youjun Zhao, Alex Warren, Gary K. L. Tam, Rynson W. H. Lau

cs.CV, cs.LG

Submitted: 2026-08-07

Updated: 2026-08-10

Comments: Project Page: https://youjunzhao.github.io/MirrorWorld/

Code: https://github.com/black-forestlabs/flux

Project page: https://youjunzhao.github.io/MirrorWorld

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 20× in this paper · explained in 2 episodes
• Diffusion Model — 19× in this paper · explained in 10 episodes
• Diffusion Models — 18× in this paper · explained in 9 episodes
• Ablation — 15× in this paper · explained in 1 episode
• Foundation Model — 13× in this paper · explained in 3 episodes
• Consistency — 12× in this paper · explained in 3 episodes
• Distillation — 10× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 9× in this paper
• Geometric Transformation Alignment — 8× in this paper
• Semantic Relation Distillation — 8× in this paper
• Transformer — 7× in this paper · explained in 2 episodes
• Temporal Consistency — 6× in this paper · explained in 3 episodes
• DINOv3 — 4× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Ablation Study — 3× in this paper · explained in 3 episodes
• Optical Flow — 3× in this paper · explained in 2 episodes
• Transformers — 3× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 2× in this paper
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 3 episodes
• Generator — 2× in this paper · explained in 2 episodes
• Localization — 2× in this paper · explained in 2 episodes
• Papers — 2× in this paper · explained in 3 episodes
• Peak Signal-to-Noise Ratio — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Coherence — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Evaluation Protocol — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 8 episodes
• Latent Diffusion Model — 1× in this paper · explained in 3 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Learned Perceptual Image Patch Similarity — 1× in this paper
• Prompt Engineering — 1× in this paper · explained in 6 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Structural Similarity Index Measure — 1× in this paper
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Temporal Stability — 1× in this paper · explained in 2 episodes
• Training Objective — 1× in this paper · explained in 3 episodes
• Weight Decay — 1× in this paper · explained in 2 episodes

Sources

• LTX-Video: Realtime Video Latent Diffusion
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• DINOv3
• Towards Accurate Generative Models of Video: A New Metric & Challenges
• Wan: Open and Advanced Large-Scale Video Generative Models

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