Skip to content

[RA-L 2026] JustDepth: Real-Time Radar-Camera Depth Estimation with Single-Scan LiDAR Supervision

License

Notifications You must be signed in to change notification settings

TPyun/JustDepth

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

JustDepth: Real-Time Radar-Camera Depth Estimation With Single-Scan LiDAR Supervision

JustDepth is a real-time radar–camera fusion model for depth estimation trained with single-scan LiDAR supervision on nuScenes.
It focuses on a strong accuracy–latency trade-off for autonomous driving perception.

  • Task: radar–camera depth estimation
  • Inputs: automotive radar returns + RGB image
  • Supervision: single-scan LiDAR
  • Dataset: nuScenes
  • Venue: IEEE Robotics and Automation Letters (RA-L), Vol. 11, No. 3, March 2026, pp. 2770–2777
  • DOI: 10.1109/LRA.2026.3655274
  • IEEE Xplore: https://ieeexplore.ieee.org/abstract/document/11358657

Demo Video

JustDepth Demo


Architecture

JustDepth Architecture


Results

Results


Runtime vs Accuracy

Latency vs MAE


Benchmark Table

Benchmark Table


Dataset (nuScenes)

This project uses the nuScenes dataset.

Data Layout

Place the nuScenes dataset under data/nuscenes/.
All required .pkl files must be placed directly under the data/ directory.

Example structure:

JustDepth/
  data/
    nuscenes/samples/
    *.pkl

Downloads


Installation

  • Python: 3.11.13

Setup

# (Recommended) create a clean environment
# conda create -n justdepth python=3.11.13 -y
# conda activate justdepth

# install dependencies
pip install -r requirements.txt

Training

Multi-GPU training (torchrun)

CUDA_VISIBLE_DEVICES=<GPU_IDS> torchrun --nproc_per_node=<NUM_GPUS> train.py
# Example:
# CUDA_VISIBLE_DEVICES=0,1 torchrun --nproc_per_node=2 train.py

Single-GPU training

CUDA_VISIBLE_DEVICES=<GPU_ID> python train.py
# Example:
# CUDA_VISIBLE_DEVICES=0 python train.py

Evaluation

Evaluate with a checkpoint:

python eval.py --checkpoint <PATH_TO_CKPT>
# Example:
# python eval.py --checkpoint /path/to/latest.ckpt

Citation

If you find this work useful, please cite:

@ARTICLE{11358657,
  author={Yun, Wooyung and Kim, Dongwook and Lee, Soomok},
  journal={IEEE Robotics and Automation Letters},
  title={JustDepth: Real-Time Radar-Camera Depth Estimation With Single-Scan LiDAR Supervision},
  year={2026},
  volume={11},
  number={3},
  pages={2770-2777},
  doi={10.1109/LRA.2026.3655274}
}