Soon122/PanoCARLA
Updated • 30 • 1
How to use Soon122/PVDepth with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Soon122/PVDepth", torch_dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]This repository provides the UNet checkpoint for PVDepth: Panoramic Video Depth Estimation via Geometry-Aware Spatiotemporal Adaptation. It estimates temporally consistent relative inverse depth from equirectangular images and videos.
GPU_ID=0 bash run_infer_any.sh \
<input_path> \
Soon122/PVDepth \
./outputs
See the PVDepth repository for installation and usage. The training dataset is available at PanoCARLA.
@inproceedings{song2026pvdepth,
author = {Song, Chuanxin and Peng, Peixi},
title = {PVDepth: Panoramic Video Depth Estimation via Geometry-Aware Spatiotemporal Adaptation},
booktitle = {ICML},
year = {2026}
}
This checkpoint is subject to the upstream licenses of DepthCrafter and Stable Video Diffusion. See the PVDepth repository for details.
Base model
tencent/DepthCrafter