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20162022
most citedNeural Rerendering in the Wild

9 citations · 30 across the 6 of their papers we have counts for

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10 papers · 1 filter

cs.CV20221 cited

RANA: Relightable Articulated Neural Avatars

Umar Iqbal, Akin Caliskan, Koki Nagano +3

We propose RANA, a relightable and articulated neural avatar for the photorealistic synthesis of humans under arbitrary viewpoints, body poses, and lighting. We only require a shor…

cs.CV20222 cited

DRaCoN -- Differentiable Rasterization Conditioned Neural Radiance Fields for Articulated Avatars

Amit Raj, Umar Iqbal, Koki Nagano +4

Acquisition and creation of digital human avatars is an important problem with applications to virtual telepresence, gaming, and human modeling. Most contemporary approaches for av…

cs.CV20219 cited

DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer

Wenzheng Chen, Joey Litalien, Jun Gao +5

We consider the challenging problem of predicting intrinsic object properties from a single image by exploiting differentiable renderers. Many previous learning-based approaches fo…

cs.CV2021

3DStyleNet: Creating 3D Shapes with Geometric and Texture Style Variations

Kangxue Yin, Jun Gao, Maria Shugrina +2

We propose a method to create plausible geometric and texture style variations of 3D objects in the quest to democratize 3D content creation. Given a pair of textured source and ta…

cs.CV20209 cited

RePose: Learning Deep Kinematic Priors for Fast Human Pose Estimation

Hossam Isack, Christian Haene, Cem Keskin +4

We propose a novel efficient and lightweight model for human pose estimation from a single image. Our model is designed to achieve competitive results at a fraction of the number o…

cs.CV20199 cited

Neural Rerendering in the Wild

Moustafa Meshry, Dan B Goldman, Sameh Khamis +4

We explore total scene capture -- recording, modeling, and rerendering a scene under varying appearance such as season and time of day. Starting from internet photos of a tourist l…