Show HN: FeyNoBg – Automatic background removal model and training library
4 hours ago
- FeyNoBg is a state-of-the-art model for automatic background removal, achieving the best S-measure on four of eight benchmarks and within 2% on the remaining four.
- The model requires two complementary skills: foreground recognition (separating subject from background) and boundary precision (image matting for edges like hair or motion blur).
- FeyNoBg builds on BiRefNet architecture, expanding the third feature extraction stage from 18 to 24 blocks (263M parameters) to improve information retention without forgetting prior knowledge.
- A diverse training dataset of 26.1K images from 10 sources was assembled, with each source capped at 4,000 images and annotations converted to binary masks to ensure consistency.
- The NoBg library provides a unified Python interface for running and training background removal models, offering higher throughput and lower latency than the original BiRefNet implementation.
- Both FeyNoBg and NoBg are open source, available on Hugging Face and GitHub respectively.