DreamHuman: Animatable 3D Avatars from Text
We present DreamHuman, a method to generate realistic animatable 3D human
avatar models solely from textual descriptions. Recent text-to-3D methods have
made considerable strides in generation, but are still lacking in important
aspects. Control and often spatial resolution remain limited, existing methods
produce fixed rather than animated 3D human models, and anthropometric
consistency for complex structures like people remains a challenge. DreamHuman
connects large text-to-image synthesis models, neural radiance fields, and
statistical human body models in a novel modeling and optimization framework.
This makes it possible to generate dynamic 3D human avatars with high-quality
textures and learned, instance-specific, surface deformations. We demonstrate
that our method is capable to generate a wide variety of animatable, realistic
3D human models from text. Our 3D models have diverse appearance, clothing,
skin tones and body shapes, and significantly outperform both generic
text-to-3D approaches and previous text-based 3D avatar generators in visual
fidelity. For more results and animations please check our website at
https://dream-human.github.io.
648c00c8f11318e0a44bcc79
Nikos Kolotouros
claimed_verified
2023-06-19T07:15:43.820Z
648cd29f8f46d7284544083b
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Nikos Kolotouros
user
kolotouros
648c00c8f11318e0a44bcc7a
Thiemo Alldieck
claimed_verified
2023-06-16T17:38:24.141Z
648c964d39d2584ee47af19c
https://cdn-avatars.huggingface.co/v1/production/uploads/648c964d39d2584ee47af19c/5UEkzDTMY8I3svKjR7kxN.jpeg
Thiemo Alldieck
user
thiemoall
648c00c8f11318e0a44bcc7b
Andrei Zanfir
claimed_verified
2023-06-19T07:15:48.199Z
648cd24dab8e3024f5bbe93b
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Andrei Zanfir
user
Andreiz
648c00c8f11318e0a44bcc7c
Eduard Gabriel Bazavan
648c00c8f11318e0a44bcc7d
Mihai Fieraru
648c00c8f11318e0a44bcc7e
Cristian Sminchisescu
DreamHuman: Animatable 3D Avatars from Text
We present DreamHuman, a method to generate realistic animatable 3D human
avatar models solely from textual descriptions. Recent text-to-3D methods have
made considerable strides in generation, but are still lacking in important
aspects. Control and often spatial resolution remain limited, existing methods
produce fixed rather than animated 3D human models, and anthropometric
consistency for complex structures like people remains a challenge. DreamHuman
connects large text-to-image synthesis models, neural radiance fields, and
statistical human body models in a novel modeling and optimization framework.
This makes it possible to generate dynamic 3D human avatars with high-quality
textures and learned, instance-specific, surface deformations. We demonstrate
that our method is capable to generate a wide variety of animatable, realistic
3D human models from text. Our 3D models have diverse appearance, clothing,
skin tones and body shapes, and significantly outperform both generic
text-to-3D approaches and previous text-based 3D avatar generators in visual
fidelity. For more results and animations please check our website at
https://dream-human.github.io.
 DreamHuman generates realistic animatable 3D human avatars using text by integrating text-to-image synthesis, neural radiance fields, and statistical human body models.
text-to-3D methods neural radiance fields statistical human body models animatable 3D human models high-quality textures instance-specific surface deformations visual fidelity