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20212025
most citedMetric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation

214 citations · 243 across the 6 of their papers we have counts for

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cs.CV2025

ReCamDriving: LiDAR-Free Camera-Controlled Video Synthesis for Novel Trajectories

Yaokun Li, Shuaixian Wang, Mantang Guo +6

Synthesizing multi-pass videos is important for autonomous driving. While current repair-based methods often struggle with out-of-distribution artifacts, camera-controlled methods…

cs.CV2024★ 214 cited

Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation

Mu Hu, Wei Yin, Chi Zhang +7

We introduce Metric3D v2, a geometric foundation model for zero-shot metric depth and surface normal estimation from a single image, which is crucial for metric 3D recovery. While…

cs.CV2024

GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Image

Xiao Fu, Wei Yin, Mu Hu +6

We introduce GeoWizard, a new generative foundation model designed for estimating geometric attributes, e.g., depth and normals, from single images. While significant research has…

cs.CV2022★ 3 cited

Online Convolutional Re-parameterization

Mu Hu, Junyi Feng, Jiashen Hua +4

Structural re-parameterization has drawn increasing attention in various computer vision tasks. It aims at improving the performance of deep models without introducing any inferenc…

cs.CV2021★ 24 cited

PENet: Towards Precise and Efficient Image Guided Depth Completion

Mu Hu, Shuling Wang, Bin Li +3

Image guided depth completion is the task of generating a dense depth map from a sparse depth map and a high quality image. In this task, how to fuse the color and depth modalities…

cs.CV2021★ 2 cited

Self-supervised Visual-LiDAR Odometry with Flip Consistency

Bin Li, Mu Hu, Shuling Wang +2

Most learning-based methods estimate ego-motion by utilizing visual sensors, which suffer from dramatic lighting variations and textureless scenarios. In this paper, we incorporate…