216 citations · 351 across the 16 of their papers we have counts for
6 papers · 1 filter
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…
The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation
Saurabh Saxena, Charles Herrmann, Junhwa Hur +4
Denoising diffusion probabilistic models have transformed image generation with their impressive fidelity and diversity. We show that they also excel in estimating optical flow and…
Unsupervised Semantic Correspondence Using Stable Diffusion
Eric Hedlin, Gopal Sharma, Shweta Mahajan +4
Text-to-image diffusion models are now capable of generating images that are often indistinguishable from real images. To generate such images, these models must understand the sem…
: 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…
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…
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…