most citedLearning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos

1 citations · 2 across the 5 of their papers we have counts for

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5 papers

cs.CL20241 cited

Generative AI-Based Text Generation Methods Using Pre-Trained GPT-2 Model

Rohit Pandey, Hetvi Waghela, Sneha Rakshit +5

This work delved into the realm of automatic text generation, exploring a variety of techniques ranging from traditional deterministic approaches to more modern stochastic methods.…

cs.CV2024

Efficient 3D Implicit Head Avatar with Mesh-anchored Hash Table Blendshapes

Ziqian Bai, Feitong Tan, Sean Fanello +5

3D head avatars built with neural implicit volumetric representations have achieved unprecedented levels of photorealism. However, the computational cost of these methods remains a…

cs.CV2024

One2Avatar: Generative Implicit Head Avatar For Few-shot User Adaptation

Zhixuan Yu, Ziqian Bai, Abhimitra Meka +6

Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge…

cs.CV2023

Controllable Light Diffusion for Portraits

David Futschik, Kelvin Ritland, James Vecore +5

We introduce light diffusion, a novel method to improve lighting in portraits, softening harsh shadows and specular highlights while preserving overall scene illumination. Inspired…

cs.CV20231 cited

Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos

Ziqian Bai, Feitong Tan, Zeng Huang +12

We propose a method to learn a high-quality implicit 3D head avatar from a monocular RGB video captured in the wild. The learnt avatar is driven by a parametric face model to achie…