Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion

arXiv:2605.04412 · cs.CV · Submitted 2026-05-06 · Read on arXiv

cs.CV

Submitted: 2026-05-06

Updated: 2026-09-23

Terminology

• Diffusion Model — 27× in this paper · explained in 8 episodes
• Generative Model — 24× in this paper · explained in 2 episodes
• Diffusion Models — 21× in this paper · explained in 6 episodes
• Generative Models — 20× in this paper · explained in 2 episodes
• Transformer — 14× in this paper · explained in 2 episodes
• Distillation — 13× in this paper · explained in 2 episodes
• Latent Space — 10× in this paper · explained in 7 episodes
• Fidelity — 9× in this paper · explained in 2 episodes
• Latent Representation — 8× in this paper · explained in 2 episodes
• Latent Diffusion Model — 6× in this paper · explained in 2 episodes
• Latent Representations — 6× in this paper · explained in 3 episodes
• Stable Diffusion — 5× in this paper
• Attention Mechanism — 4× in this paper · explained in 3 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Gaussian Splatting — 4× in this paper · explained in 4 episodes
• Latent Diffusion Models — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• alpha — 3× in this paper · explained in 1 episode
• Ablation — 2× in this paper · explained in 1 episode
• Cross-Attention Mechanism — 2× in this paper · explained in 2 episodes
• Flow Matching — 2× in this paper · explained in 8 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Rectified Flow — 2× in this paper · explained in 3 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Latent Diffusion Model (LDM) — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Vision-Language Model (VLM) — 1× in this paper · explained in 3 episodes

Sources

• Denoising Diffusion Implicit Models
• Advances in 3D Generation: A Survey
• DreamFusion: Text-to-3D using 2D Diffusion
• UniLat3D: Geometry-Appearance Unified Latents for Single-Stage 3D Generation
• Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
• MorphAny3D: Unleashing the Power of Structured Latent in 3D Morphing
• Score-Based Generative Modeling through Stochastic Differential Equations
• SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
• Flow Matching for Generative Modeling
• Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
• DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation
• Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model
• MVDream: Multi-view Diffusion for 3D Generation
• LRM: Large Reconstruction Model for Single Image to 3D
• IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
• An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
• StyleSplat: 3D Object Style Transfer with Gaussian Splatting
• Fix False Transparency by Noise Guided Splatting
• Object-Centric 2D Gaussian Splatting: Background Removal and Occlusion-Aware Pruning for Compact Object Models
• InstantStyle-Plus: Style Transfer with Content-Preserving in Text-to-Image Generation

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