Skip to content

ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling [ICCV 2025]

License

rdbch/claravid_code

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

22 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ClaraVid

Project Page Hugging Face arXiv Preprint

If you find this useful, please consider giving us a star ⭐

Official repo for: ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling - Accepted ICCV 2025

ClaraVid Overview

ClaraVid is a synthetic dataset built for semantic and geometric neural reconstruction from low altitude UAV/aerial imagery. It contains 16,917 multimodal frames collected across 8 UAV missions over 5 diverse environments: urban, urban high, rural, highway, and nature.

Delentropic Scene Profile (DSP) is a metric for estimating scene complexity from images, tailored for structured UAV mapping scenarios. DSP helps predict reconstruction difficulty.

Channel Log / TODOs

  • All data uploaded
  • Release dataset SDK
  • Release pip package
  • Release DSP code
  • Add Nerfstudio support (after conference)

Installation

Easiest way to install this package is to use pip:

# just for dataset interface
pip install claravid 

# for dataset interface + complexity profiles of a scene (you will likely want this)
pip install claravid[dsp]

# for dataset interface + complexity profiles of a scene + examples (includes open3d)
pip install claravid[all]

Alternatively you can clone the repository and install it manually:

git clone https://github.com/rdbch/claravid_code.git
pip install -e . 

pip install -e .[dsp] 

pip install -e .[all] 

Examples

Compute complexity scene profile

We provide a script for computing and plotting the complexity profile of a given scene. We support currently 3 complexity functions: delentropy, GLCM entropy and Pixel Shannon entropy. See ./scene_complexity_profile.py for more details regarding the implementation.

# compute and generate DSP plot
$ python ./scripts/compute_complexity_profile.py --input /path/to/input --pattern *.jpg --complexity_func delent

# compute DSP for scene 003_urban_1
$ python ./scripts/compute_complexity_profile.py --input /path/to/claravid/003_urban_1 --pattern left_rgb/**/*.jpg --complexity_func delent

Dataset interface

We provide 2 examples for this dataset code base:

Dataset interface

In examples/demo.ipynb we provide an example for loading and exploring a scene and configuring the various flight parameters and modalities:

from claravid import ClaravidDataset

dataset = ClaravidDataset(
    root=Path('/path/to/claravid'),
    missions=['highway_1', ],     # see ClaravidMissions
    altitude=['low', ],           # see ClaravidAltitude
    direction=['v', 'h'],         # see ClaravidGridDirection
    fields=['rgb', 'pan_seg', 'depth', ...],
)
data = dataset[0]
{"rgb":..., "pan_seg":..., "depth":..., ...}

3D Manipulation

In examples/pcl_project.py we provide an example for loading the scene PCL and projecting it to back to a certain frame. This serves as an example on how to handle extrinsics, 3D un/projection and manipulating scene pointclouds.

Bibtex

If you found this work useful, please cite us as:

@misc{beche2025claravid,
  title={ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling},
  author={Beche, Radu and Nedevschi, Sergiu},
  journal={arXiv preprint arXiv:2503.17856},
  year={2025}
}

About

ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling [ICCV 2025]

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages