Depth Completion

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2 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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LiDAR Resolution Recovery via Foundation-Model-Guided Diffusion
Oct 6, 2026Samed Doğan, Nico Leuze, Alfred SchöttlDiffusion Model Guidance Depth Completion
Dept. of Electrical Engineering and Information Technology Munich University of Applied Sciences, 80335 Munich, Germany
Boosting Metric Depth Completion via Training-Free Adaptive Response Geometry
Sep 28, 2026Mia Zhang, Jizong PengPost-Hoc Calibration Depth Completion
dConstruct Robotics · University of Waterloo
FounRef: Robust, Structure-Preserving, and Fast Metric Refinement of Frozen Monocular Foundation Priors with Sparse Anchors
Sep 24, 2026Dan Halperin, Mirko MählischMetric Depth Estimation Depth Completion
University of the Bundeswehr Munich, Germany
SG-AMP: Scene-Graph-Guided Active Perception and Semantics-Aware Motion Planning for Pepper Plants
Sep 1, 2026Rohit Menon, Shiva Rudra Lolla, Niklas Mueller-Goldingen +3Depth Completion Agricultural Robotics
Humanoid Robots Lab, University of Bonn, Germany · Center for Robotics, Bonn, Germany · Institute of Geodesy and Geoinformation, University of Bonn +1
RbFT-Net: Rectify-Before-Fuse Temporal Radar Anchors for 4D Radar-Camera Depth Completion
Aug 13, 2026Wentao Zhao, Shouxuan Wu, Yongtao Cen +3Camera-Radar Fusion Metric Depth Estimation
School of Automation and Intelligent Sensing, Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China · School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China · 3State Key Laboratory of Advanced Rail Autonomous Operation and School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
Dense Metric Depth Completion from Sparse Direct Time-of-Flight Sensors
Aug 5, 2026Hakyeong Kim, Ruicheng Wang, Chengtang Yao +2Metric Depth Estimation Depth Estimation
KAIST · USTC · Microsoft Research Asia
AISPO: Enhancing Depth Reliability for Robotic Manipulation of Non-Lambertian Objects via Affine-Invariant Shape Prior
Jun 24, 2026Zhiming Chen, Linfang Zheng, Kun Zhang +4Depth Completion Robotic Manipulation
The Hong Kong University of Science & Technology · LimX Dynamics · The University of Hong Kong +2
ShotcreteDepth: A Bi-modal Dataset for Robust Robotic Depth Perception in Shotcrete Construction Environments
Jun 22, 2026Jakub Gregorek, Lars Arnold Dethlefsen, Patrick Schmidt +3Robotic Construction Depth Estimation
1Technical University of Denmark, Department of Electrical and Photonics Engineering. · 2Pioneer Centre for AI, Copenhagen, Denmark. · 3Christiansen & Essenbæk A/S.
Honey, I Shrunk the Arc de Triomphe!
Jun 1, 2026Yuanbo Xiangli, Hanyu Chen, Xueqing Tsang +13D Foundation Models Metric Depth Estimation
Cornell University · Shanghai Jiao Tong University
Large Depth Completion Model from Sparse Observations
May 28, 2026Zhu Yu, Zhengyi Zhao, Runmin Zhang +7Metric Depth Estimation Depth Estimation
Zhejiang University · Internship at Tongyi Lab · Tongyi Lab, Alibaba Group +4
WideDepth: Millimeter-Accurate Benchmark for Fisheye Depth Estimation
May 22, 2026Ilia Indyk, Ignat Penshin, Ivan Sosin +3Metric Depth Estimation Depth Estimation
Robotics Center, Moscow, Russia · AXXX, Moscow, Russia · Trusted AI Research Center, RAS, Moscow, Russia
CARD: A Multi-Modal Automotive Dataset for Dense 3D Reconstruction in Challenging Road Topography
May 6, 2026Gasser Elazab, Frank Neuhaus, Tilman Koß +5Autonomous Driving Datasets Autonomous Driving Benchmarks
1CARIAD SE · 2Technische Universität Berlin · 3Vision & Robotics GmbH
EfficientPENet: Real-Time Depth Completion from Sparse LiDAR via Lightweight Multi-Modal Fusion
Apr 20, 2026Johny J. Lopez, Md Meftahul Ferdaus, Mahdi Abdelguerfi +4Efficient Neural Network Inference Depth Estimation
Canizaro Livingston Gulf States Center for Environmental Informatics, the University of New Orleans, New Orleans, USA · US Army Corps of Engineers, Engineer Research and Development Center, Vicksburg, Mississippi, USA
Fringe Projection Based Vision Pipeline for Autonomous Hard Drive Disassembly
Apr 19, 2026Badrinath Balasubramaniam, Vignesh Suresh, Benjamin Metcalf +1Fringe Projection Profilometry 3D Reconstruction
School of Electrical and Computer Engineering, University of Georgia, Athens, 30605, GA, USA · Alcon Research Laboratories, Fort Worth, 76134, Texas, USA · University of Georgia, Athens, 30605, GA, USA +1
MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources
Jan 29, 2026Baorui Ma, Jiahui Yang, Donglin Di +5Vision Foundation Models Metric Depth Estimation
Li Auto Inc
Gaussian Belief Propagation Network for Depth Completion
Date pendingJie Tang, Pingping Xie, Jian Li +1Markov Random Fields Depth Estimation
National University of Defense Technology, Changsha, China · Hong Kong University of Science and Technology, Hong Kong, China

Oct 6, 2026, cs.CVJ/K move · Enter open · S save

LiDAR Resolution Recovery via Foundation-Model-Guided Diffusion

Samed Doğan, Nico Leuze, Alfred Schöttl

Dept. of Electrical Engineering and Information Technology Munich University of Applied Sciences, 80335 Munich, Germany

Diffusion Model Guidance Depth Completion Diffusion Model Fine-Tuning

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High-beam-count LiDAR sensors are costly, yet many perception pipelines require dense angular sampling. Using a pretrained Stable Diffusion model as the backbone, we fine-tune a LiDAR-conditioned depth model with pseudo-depth targets from a 2D foundation model. During training, the LiDAR conditioning is randomly decimated at different beam budgets. We then investigate how much of a LiDAR scan can be recovered from heavily decimated input and characterize performance across the input beam budget. We evaluate against physically held-out real beams on nuScenes and report recovery separately from fit accuracy. Our model yields its largest advantage in very sparse regimes, achieving a

δ_{1.25}

accuracy of

66.8

% from

4

-beam input where scattered interpolation reaches only

45.1

%. A class-stratified error breakdown further reveals that planar surfaces recover first while objects introducing depth discontinuities degrade earliest. Together, these results quantify the recovery/resolution trade-off for foundation-model-guided LiDAR enhancement.

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