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20192026
most citedZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

175 citations · 216 across the 6 of their papers we have counts for

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cs.CV2025

Rapid Salient Object Detection with Difference Convolutional Neural Networks

Zhuo Su, Li Liu, Matthias Müller +4

This paper addresses the challenge of deploying salient object detection (SOD) on resource-constrained devices with real-time performance. While recent advances in deep neural netw…

cs.CV2024★ 2 cited

L-MAGIC: Language Model Assisted Generation of Images with Coherence

Zhipeng Cai, Matthias Mueller, Reiner Birkl +6

In the current era of generative AI breakthroughs, generating panoramic scenes from a single input image remains a key challenge. Most existing methods use diffusion-based iterativ…

cs.CV2023★ 37 cited

MiDaS v3.1 -- A Model Zoo for Robust Monocular Relative Depth Estimation

Reiner Birkl, Diana Wofk, Matthias Müller

We release MiDaS v3.1 for monocular depth estimation, offering a variety of new models based on different encoder backbones. This release is motivated by the success of transformer…

cs.CV2023★ 2 cited

Monocular Visual-Inertial Depth Estimation

Diana Wofk, René Ranftl, Matthias Müller +1

We present a visual-inertial depth estimation pipeline that integrates monocular depth estimation and visual-inertial odometry to produce dense depth estimates with metric scale. O…

cs.CV2023★ 175 cited

ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

Shariq Farooq Bhat, Reiner Birkl, Diana Wofk +2

This paper tackles the problem of depth estimation from a single image. Existing work either focuses on generalization performance disregarding metric scale, i.e. relative depth es…

cs.CV2019

FastDepth: Fast Monocular Depth Estimation on Embedded Systems

Diana Wofk, Fangchang Ma, Tien-Ju Yang +2

Depth sensing is a critical function for robotic tasks such as localization, mapping and obstacle detection. There has been a significant and growing interest in depth estimation f…