Falcon Perception
This article from the Hugging Face Blog introduces Falcon Perception, a compact 0.6B-parameter early-fusion Transformer model designed for open-vocabulary grounding and segmentation. The model processes image patches and text in a single sequence using a hybrid attention mask, producing variable instances with a structured token interface. It achieves 68.0 Macro-F1 on the SA-Co benchmark, outperforming SAM 3. The article also introduces PBench, a diagnostic benchmark for evaluating perception capabilities, and Falcon OCR, a 0.3B-parameter OCR model with high throughput. The post provides a detailed architectural overview and experimental results.
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