activity
20222024
most citedMetric3D: Towards Zero-shot Metric 3D Prediction from A Single Image

4 citations · 10 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV20241 cited

LaserHuman: Language-guided Scene-aware Human Motion Generation in Free Environment

Peishan Cong, Ziyi Wang, Zhiyang Dou +7

Language-guided scene-aware human motion generation has great significance for entertainment and robotics. In response to the limitations of existing datasets, we introduce LaserHu…

cs.CV2023

Robust Geometry-Preserving Depth Estimation Using Differentiable Rendering

Chi Zhang, Wei Yin, Gang Yu +5

In this study, we address the challenge of 3D scene structure recovery from monocular depth estimation. While traditional depth estimation methods leverage labeled datasets to dire…

cs.CV20231 cited

FrozenRecon: Pose-free 3D Scene Reconstruction with Frozen Depth Models

Guangkai Xu, Wei Yin, Hao Chen +3

3D scene reconstruction is a long-standing vision task. Existing approaches can be categorized into geometry-based and learning-based methods. The former leverages multi-view geome…

cs.CV20234 cited

Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image

Wei Yin, Chi Zhang, Hao Chen +5

Reconstructing accurate 3D scenes from images is a long-standing vision task. Due to the ill-posedness of the single-image reconstruction problem, most well-established methods are…

cs.CV2023

The Second Monocular Depth Estimation Challenge

Jaime Spencer, C. Stella Qian, Michaela Trescakova +40

This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC). This edition was open to methods using any form of supervision, includin…

cs.CV2023

Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes

Rui Li, Dong Gong, Wei Yin +6

Multi-frame depth estimation generally achieves high accuracy relying on the multi-view geometric consistency. When applied in dynamic scenes, e.g., autonomous driving, this consis…