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Fine-tune YOLO-World on MS-COCO

Updates

  1. [2024-3-27]: Considering that fine-tuning YOLO-World on COCO without mask-refine obtains bad results, e.g., YOLO-World-L obtains 48.6 AP without mask-refine compared to 53.3 AP with mask-refine, we rethink the training process and explore new training schemes for fine-tuning without mask-refine. BTW, the COCO fine-tuning results are updated with higher performance (with mask-refine)!

COCO Results and Checkpoints

NOTE:

  1. APZS: AP evaluated in the zero-shot setting (w/o fine-tuning on COCO dataset).
  2. mask-refine: refine the box annotations with masks, and add CopyPaste augmentation during training.
model Schedule mask-refine efficient neck APZS AP AP50 AP75 weights log
YOLO-World-v2-S AdamW, 2e-4, 80e ✔️ ✖️ 37.5 46.1 62.0 49.9 HF Checkpoints log
YOLO-World-v2-M AdamW, 2e-4, 80e ✔️ ✖️ 42.8 51.0 67.5 55.2 HF Checkpoints log
YOLO-World-v2-L AdamW, 2e-4, 80e ✔️ ✖️ 45.1 53.9 70.9 58.8 HF Checkpoints log
YOLO-World-v2-X AdamW, 2e-4, 80e ✔️ ✖️ 46.8 54.7 71.6 59.6 HF Checkpoints log
YOLO-World-v2-L 🔥 SGD, 1e-3, 40e ✖️ ✖️ 45.1 52.8 69.5 57.8 HF Checkpoints log

Reparameterized Training

model Schedule mask-refine efficient neck APZS AP AP50 AP75 weights log
YOLO-World-v2-S AdamW, 2e-4, 80e ✔️ ✖️ 37.5 46.3 62.8 50.4 HF Checkpoints log