ZoomDiff: A High-Fidelity Diffusion Model for Dual-Camera Smooth Zooming

arXiv:2609.28083 · cs.CV · Submitted 2026-09-23 · Read on arXiv

cs.CV

Submitted: 2026-09-23

Updated: 2026-09-23

Project page: https://jiayi-hit.github.io/ZoomDiff.github.io

Terminology

• Fidelity — 20× in this paper · explained in 2 episodes
• Diffusion Model — 18× in this paper · explained in 8 episodes
• Consistency — 17× in this paper · explained in 3 episodes
• Temporal consistency — 11× in this paper · explained in 2 episodes
• Adaptation — 10× in this paper · explained in 1 episode
• Diffusion Models — 10× in this paper · explained in 6 episodes
• Latent Space — 10× in this paper · explained in 7 episodes
• Optical Flow — 8× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Dual-Camera Smooth Zoom — 5× in this paper
• Transformer — 4× in this paper · explained in 2 episodes
• Diffusion Process — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• 3D Gaussian Splatting — 1× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Cross-Attention Mechanism — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Gaussian Splatting — 1× in this paper · explained in 4 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Taking Stable Video Diffusion — 1× in this paper
• Two-Stage Training Strategy — 1× in this paper · explained in 3 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes

Sources

• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• VideoCrafter1: Open Diffusion Models for High-Quality Video Generation
• Adam: A Method for Stochastic Optimization
• CAT: Cross Attention in Vision Transformer
• Learning Transferable Visual Models From Natural Language Supervision
• Towards Accurate Generative Models of Video: A New Metric & Challenges
• Wan: Open and Advanced Large-Scale Video Generative Models
• Framer: Interactive Frame Interpolation
• Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolation
• ViBiDSampler: Enhancing Video Interpolation Using Bidirectional Diffusion Sampler

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