ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera"

Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) [MVA 2019]

ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (PyTorch Implementation)

ICRA 2021 "Towards Precise and Efficient Image Guided Depth Completion"

Sparse Fuse Dense: Towards High Quality 3D Detection with Depth Completion (CVPR 2022, Oral)

Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)

🍀 Official pytorch implementation of "Indoor Depth Completion with Boundary Consistency and Self-Attention. Huang et al. RLQ@ICCV 2019."

PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)

[RAL 2022 & ICRA 2023] TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and A Grasping Baseline

Unofficial Faster PyTorch implementation of Convolutional Spatial Propagation Network

Official page of Struct-MDC (RA-L'22 with IROS'22); Depth completion from Visual-SLAM using point & line features

PyTorch Implementation of Monitored Distillation for Positive Congruent Depth Completion (ECCV 2022)

NeurIPS 2019: Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion

Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)

Depth Completion technique agnostic to input depth pattern sparsity, WACV23

[3DV 2024] Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization

Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20. model in ONNX

ICASSP 2021: Scene Completeness-Aware Lidar Depth Completion for Driving Scenario

CVPR 2024: Robust Depth Enhancement via Polarization Prompt Fusion Tuning

Attentive Bilateral Convolutional Network for Robust Depth Completion