activity
20192024
most citedMetric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation

214 citations · 252 across the 19 of their papers we have counts for

collaborators
Showing 2022Show all

11 papers · 1 filter

cs.CV2022★ 4 cited

SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenes

Libo Sun, Jia-Wang Bian, Huangying Zhan +3

Self-supervised monocular depth estimation has shown impressive results in static scenes. It relies on the multi-view consistency assumption for training networks, however, that is…

cs.CV2022★ 8 cited

Hierarchical Normalization for Robust Monocular Depth Estimation

Chi Zhang, Wei Yin, Zhibin Wang +3

In this paper, we address monocular depth estimation with deep neural networks. To enable training of deep monocular estimation models with various sources of datasets, state-of-th…

cs.CV2022★ 3 cited

Towards Accurate Reconstruction of 3D Scene Shape from A Single Monocular Image

Wei Yin, Jianming Zhang, Oliver Wang +4

Despite significant progress made in the past few years, challenges remain for depth estimation using a single monocular image. First, it is nontrivial to train a metric-depth pred…

cs.CV2022★ 1 cited

Controllable Shadow Generation Using Pixel Height Maps

Yichen Sheng, Yifan Liu, Jianming Zhang +6

Shadows are essential for realistic image compositing. Physics-based shadow rendering methods require 3D geometries, which are not always available. Deep learning-based shadow synt…

cs.CV2022★ 4 cited

Towards Domain-agnostic Depth Completion

Guangkai Xu, Wei Yin, Jianming Zhang +4

Existing depth completion methods are often targeted at a specific sparse depth type and generalize poorly across task domains. We present a method to complete sparse/semi-dense, n…

cs.CV2022★ 2 cited

Exploiting Correspondences with All-pairs Correlations for Multi-view Depth Estimation

Kai Cheng, Hao Chen, Wei Yin +2

Multi-view depth estimation plays a critical role in reconstructing and understanding the 3D world. Recent learning-based methods have made significant progress in it. However, mul…