From Unity Simulation to Diffusion-Based Augmentation: Quantifying Dataset Balance for Robust Object Detection
cs.CV, cs.AI
Submitted: 2026-09-29
Updated: 2026-09-29
Terminology
Sources
- Unity Perception: Generate Synthetic Data for Computer Vision
- Denoising Diffusion Probabilistic Models
- Data-Centric Artificial Intelligence
- Self-Supervised YOLO: Leveraging Contrastive Learning for Label-Efficient Object Detection
- Stable Bias: Analyzing Societal Representations in Diffusion Models
- Analyzing Bias in Diffusion-based Face Generation Models
- Learning Transferable Visual Models From Natural Language Supervision
- You Only Look Once: Unified, Real-Time Object Detection
- High-Resolution Image Synthesis with Latent Diffusion Models
- Prototypical Networks for Few-shot Learning
- Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
- Adversarial Discriminative Domain Adaptation
- Frustratingly Simple Few-Shot Object Detection
- On the Limitation of Diffusion Models for Synthesizing Training Datasets
- Adding Conditional Control to Text-to-Image Diffusion Models
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