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20172026
most citedDrag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

205 citations · 335 across the 39 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

cs.CV2023

Diffusion Posterior Illumination for Ambiguity-aware Inverse Rendering

Linjie Lyu, Ayush Tewari, Marc Habermann +4

Inverse rendering, the process of inferring scene properties from images, is a challenging inverse problem. The task is ill-posed, as many different scene configurations can give r…

cs.CV2023★ 2 cited

Approaching human 3D shape perception with neurally mappable models

Thomas P. O'Connell, Tyler Bonnen, Yoni Friedman +4

Humans effortlessly infer the 3D shape of objects. What computations underlie this ability? Although various computational models have been proposed, none of them capture the human…

cs.CV2023

AvatarStudio: Text-driven Editing of 3D Dynamic Human Head Avatars

Mohit Mendiratta, Xingang Pan, Mohamed Elgharib +6

Capturing and editing full head performances enables the creation of virtual characters with various applications such as extended reality and media production. The past few years…

cs.CV2023★ 23 cited

Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision

Ayush Tewari, Tianwei Yin, George Cazenavette +5

Denoising diffusion models are a powerful type of generative models used to capture complex distributions of real-world signals. However, their applicability is limited to scenario…

cs.CV2023★ 5 cited

FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow

Cameron Smith, Yilun Du, Ayush Tewari +1

Reconstruction of 3D neural fields from posed images has emerged as a promising method for self-supervised representation learning. The key challenge preventing the deployment of t…

cs.CV2023★ 205 cited

Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

Xingang Pan, Ayush Tewari, Thomas Leimkühler +3

Synthesizing visual content that meets users' needs often requires flexible and precise controllability of the pose, shape, expression, and layout of the generated objects. Existin…

cs.CV2023

Learning to Render Novel Views from Wide-Baseline Stereo Pairs

Yilun Du, Cameron Smith, Ayush Tewari +1

We introduce a method for novel view synthesis given only a single wide-baseline stereo image pair. In this challenging regime, 3D scene points are regularly observed only once, re…

cs.CV2023★ 4 cited

ConceptFusion: Open-set Multimodal 3D Mapping

Krishna Murthy Jatavallabhula, Alihusein Kuwajerwala, Qiao Gu +14

Building 3D maps of the environment is central to robot navigation, planning, and interaction with objects in a scene. Most existing approaches that integrate semantic concepts wit…