Cityscapes Unsupervised Panoptic Pseudo Labels Pseudo labels for unsupervised panoptic segmentation on Cityscapes, generated using overclustered k means semantics + depth guided instance splitting. Contents Pseudo Labels Directory Description Files Format pseudo semantic raw k80/ Overclustered k=80 semantic labels ~3.5K PNGs + centroids.npz PNG (values 0 79), train/val split cups pseudo labels depthpro tau020/ CUPS format combined labels (DepthPro tau=0.20) ~9K files semantic.png + instance.png + .pt per image Pre trained Weights File Description Size weights/dinov3 vitb16 official.pth DINOv3 ViT B/16 backbone (Meta official format) 327MB weights/cups.ckpt CUPS Cascade Mask R CNN checkpoint 916MB Download Pipeline 1. Semantic : DINOv2 ViT B/14 features k means (k=80) overclustering 80 class pseudo semantics 2. Instance : DepthPro monocular depth Sobel gradients threshold (tau=0.20, A min=1000) instance masks 3. CUPS format : semantic.png (mapped to 27 CAUSE classes) + instance.png + .pt (metadata) per image Metrics (Cityscapes val, 27 class CAUSE + Hungarian matching) Component PQ PQ stuff PQ things k=80 semantics + DepthPro instances 28.40 32.08 23.35 CUPS Stage 2 (trained on thes…
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