POCI-Diff: 3D-Layout Guided Diffusion for Controllable Synthetic Surveillance Data Generation

arXiv:2601.14056 · cs.CV, cs.AI · Submitted 2026-01-20 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-01-20

Updated: 2026-08-29

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

Terminology

• Consistency — 25× in this paper · explained in 3 episodes
• Diffusion Model — 19× in this paper · explained in 8 episodes
• Diffusion Models — 15× in this paper · explained in 6 episodes
• Fidelity — 11× in this paper · explained in 2 episodes
• Fine-Tuning — 9× in this paper · explained in 5 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Diffusion Processes — 3× in this paper · explained in 2 episodes
• Segmentation Masks — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Domain Shift — 2× in this paper · explained in 4 episodes
• Object Accuracy — 2× in this paper
• Ablation study — 1× in this paper · explained in 1 episode
• Active Regions — 1× in this paper · explained in 1 episode
• Analyzer — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Mean Intersection-over-Union — 1× in this paper
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes

Sources

• ARNIQA: Learning Distortion Manifold for Image Quality Assessment
• Build-A-Scene: Interactive 3D Layout Control for Diffusion-Based Image Generation
• Training-free Composite Scene Generation for Layout-to-Image Synthesis
• GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
• DINOv2: Learning Robust Visual Features without Supervision
• ESPLoRA: Enhanced Spatial Precision with Low-Rank Adaption in Text-to-Image Diffusion Models for High-Definition Synthesis
• Exploring CLIP for Assessing the Look and Feel of Images
• InstantID: Zero-shot Identity-Preserving Generation in Seconds
• HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models
• IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
• CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models
• The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

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