ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device
Paper • 2607.08771 • Published
ZipDepth (base) — pretrained checkpoints
Mirror of the official ZipDepth release checkpoints for use with
hf_hub_download (e.g. the monopriors package in rerun-io/examples-monorepo).
ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device Tosi, Bartolomei, Poggi, Mattoccia — ECCV 2026. Paper: https://arxiv.org/abs/2607.08771 · Code: https://github.com/fabiotosi92/ZipDepth (pixi fork: https://github.com/pablovela5620/ZipDepth)
| File | Upsampling | Params (fused) | Use |
|---|---|---|---|
zipdepth_base.pth |
Convex (torch.nn.Unfold) |
~6.1 M | GPU / server (upsample_unfold=True) |
zipdepth_base_npu.pth |
Convex, unfold-free | ~6.1 M | NPU / mobile / ONNX export (upsample_unfold=False) |
Both share identical encoder/decoder weights; only the upsampling head differs. Output is relative inverse depth (disparity up to scale). Trained at 384×384.
from huggingface_hub import hf_hub_download
ckpt = hf_hub_download("pablovela5620/zipdepth", "zipdepth_base.pth")
License: MIT (see LICENSE, © the ZipDepth authors).
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