DINOv3
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- Arrow detection with a ConvNeXt backbone pretrained on DINOv3
A Reddit user, BrashBunyip, posted an archery arrow-detection project on r/MachineLearning, building a dataset from roughly 40,000 rendered Blender scenes plus 8,000 hand-labelled real images, augmented into about 1 million training samples for separate registration and detection networks. The author reports that ImageNet-pretrained ResNets performed quite well and a pure ViT worse, while ConvNeXt pretrained on DINOv3 performed best. Self-reported test results were F1 96.6% and 80.5% whole-image correctness, with no missed arrows and no false detections. The pipeline registers the target to find rings, centre and scoring zones, produces an impact heatmap from the cropped image, runs the detector mirrored, applies a homography to remove perspective skew and adds a radial correction for warped paper.
r/MachineLearning · 🔥 4
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