most citedMonocular Depth Estimation using Diffusion Models

25 citations · 27 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2024

SHINOBI: Shape and Illumination using Neural Object Decomposition via BRDF Optimization In-the-wild

Andreas Engelhardt, Amit Raj, Mark Boss +8

We present SHINOBI, an end-to-end framework for the reconstruction of shape, material, and illumination from object images captured with varying lighting, pose, and background. Inv…

cs.CV20232 cited

LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs

Zezhou Cheng, Carlos Esteves, Varun Jampani +3

A critical obstacle preventing NeRF models from being deployed broadly in the wild is their reliance on accurate camera poses. Consequently, there is growing interest in extending…

cs.CV2023

: Dual-Camera Defocus Control by Learning to Refocus

Hadi Alzayer, Abdullah Abuolaim, Leung Chun Chan +4

Smartphone cameras today are increasingly approaching the versatility and quality of professional cameras through a combination of hardware and software advancements. However, fixe…

cs.CV2023

ASIC: Aligning Sparse in-the-wild Image Collections

Kamal Gupta, Varun Jampani, Carlos Esteves +4

We present a method for joint alignment of sparse in-the-wild image collections of an object category. Most prior works assume either ground-truth keypoint annotations or a large d…

cs.CV202325 cited

Monocular Depth Estimation using Diffusion Models

Saurabh Saxena, Abhishek Kar, Mohammad Norouzi +1

We formulate monocular depth estimation using denoising diffusion models, inspired by their recent successes in high fidelity image generation. To that end, we introduce innovation…