From the source
From the source
TII introduces Falcon Perception, a 0.6B-parameter early-fusion Transformer for open-vocabulary grounding and segmentation, and Falcon OCR, a 0.3B-parameter OCR model.
Falcon Perception achieves 68.0 Macro-F1 on SA-Co, beating SAM 3's 62.3.
Falcon OCR achieves 80.3 on olmOCR and 88.6 on OmniDocBench with high throughput.
They also introduce PBench, a diagnostic benchmark.
From the source
Falcon Perception is a 0.6B-parameter early-fusion Transformer for open-vocabulary grounding and segmentation from natural language prompts. The model processes image patches + text in one sequence using a hybrid attention mask, and produces variable numbers of instances with a small, structured token interface and lightweight output heads. On SA-Co, Falcon Perception reaches 68.0 Macro-F1 (vs. 62.3 for SAM 3) with the main remaining gap being presence calibration (MCC 0.64 vs. 0.82). We also introduce PBench, a diagnostic benchmark that breaks down performance by capability (attributes, OCR-guided disambiguation, spatial constraints, relations) and by dense long-context crowded scenes. We also relase Falcon OCR, a 0.3B-parameter model which reaches a score of 80.3 and 88.6 on the olmOCR benchmark and OmniDocBench respectively, while having the highest throughput of any open source OCR model.
