Gated Stereo: Joint Depth Estimation from Gated and Wide-Baseline Active Stereo Cues
Stefanie Walz, Mario Bijelic, Andrea Ramazzina, Amanpreet Walia, Fahim Mannan, Felix Heide
Abstract
We propose Gated Stereo, a high-resolution and longrange depth estimation technique that operates on active gated stereo images. Using active and high dynamic range passive captures, Gated Stereo exploits multi-view cues alongside time-of-flight intensity cues from active gating. To this end, we propose a depth estimation method with a monocular and stereo depth prediction branch which are combined in a final fusion stage. Each block is supervised through a combination of supervised and gated selfsupervision losses. To facilitate training and validation, we acquire a long-range synchronized gated stereo dataset for automotive scenarios. We find that the method achieves an improvement of more than 50 % MAE compared to the next best RGB stereo method, and 74 % MAE to existing monocular gated methods for distances up to 160 m. Our code, models and datasets are available here 1 .
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext b9d39988-72c5-414c-b004-16129abdc6b4Cited by top-tier papers6
- Self-Supervised Sparse Sensor Fusion for Long Range PerceptionEdoardo Palladin, Samuel Brucker, Filippo Ghilotti, Praveen Narayanan et al.ICCV 2025 · 4 citations
- Diving into the Fusion of Monocular Priors for Generalized Stereo MatchingChengtang Yao, Lidong Yu, Zhidan Liu, Jiaxi Zeng et al.ICCV 2025 · 3 citations
- ToF-IP: Time-of-Flight Enhanced Sparse Inertial Poser for Real-time Human Motion CaptureYuan Yao, Shifan Jiang, Yangqing Hou, Chengxu Zuo et al.NeurIPS 2025 · 2 citations
- Gated Fields: Learning Scene Reconstruction from Gated VideosAndrea Ramazzina, Stefanie Walz, Pragyan Dahal, Mario Bijelic et al.CVPR 2024 · 2 citations
- Cross-spectral Gated-RGB Stereo Depth EstimationSamuel Brucker, Stefanie Walz, Mario Bijelic, Felix HeideCVPR 2024
Builds on13
- Vision Transformers for Dense PredictionRené Ranftl, Alexey Bochkovskiy, Vladlen KoltunICCV 2021 · 2,647 citations
- Digging Into Self-Supervised Monocular Depth EstimationClément Godard, Oisin Mac Aodha, Michael Firman, Gabriel J. BrostowICCV 2019 · 2,416 citations
- Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with TransformersZhaoshuo Li, Xingtong Liu, Nathan Drenkow, Andy S. Ding et al.ICCV 2021 · 380 citations
- Attention Concatenation Volume for Accurate and Efficient Stereo MatchingGangwei Xu, Junda Cheng, Peng Guo, Xin YangCVPR 2022 · 265 citations
- Unsupervised Depth Completion with Calibrated Backprojection LayersAlex Wong, Stefano SoattoICCV 2021 · 114 citations
Related papers
- Gated3D: Monocular 3D Object Detection From Temporal Illumination CuesFrank D. Julca-Aguilar, Jason Taylor, Mario Bijelic, Fahim Mannan et al.ICCV 2021 · 16 citations
- Gated2Gated: Self-Supervised Depth Estimation from Gated ImagesAmanpreet Walia, Stefanie Walz, Mario Bijelic, Fahim Mannan et al.CVPR 2022
- GS-ASM: 2DGS-Supervised Active Stereo MatchingZhengling Wu, Rongfeng Lu, Quan Chen, Longjian Zeng et al.CVPR 2026
- Gated2Depth: Real-Time Dense Lidar From Gated ImagesTobias Gruber, Frank D. Julca-Aguilar, Mario Bijelic, Felix HeideICCV 2019 · 70 citations
- Revealing the Reciprocal Relations between Self-Supervised Stereo and Monocular Depth EstimationZhi Chen, Xiaoqing Ye, Wei Yang, Zhenbo Xu et al.ICCV 2021 · 34 citations
