FeyNoBg: A SOTA Model For Background Removal

FeyNoBg is introduced as a state-of-the-art model for automatic background removal, achieving top performance on four out of eight benchmarks and closely matching the leaders on the others. Built on the BiRefNet architecture, FeyNoBg effectively separates foregrounds from backgrounds and traces boundaries even in complex images by expanding the third stage of its feature extractor, increasing the model's capacity from 222M to 263M parameters. Training involved a diverse dataset of 26.1K images from 10 different sources to enhance its ability to handle varied scenarios, converting all annotations to binary foreground masks for consistency. The accompanying NoBg library, released open-source, facilitates running and training background removal models by providing a consistent interface, resulting in higher throughput and lower latency compared to original implementations. FeyNoBg and NoBg, developed by Feyn, allow users to easily experiment with and deploy advanced image matting solutions, with resources available on platforms like Hugging Face and GitHub.

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