Avatar Concept Slider: Controllable Editing of Concepts in 3D Human Avatars
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Abstract (arXiv)
Text-based editing of 3D human avatars to precisely match user requirements is challenging due to the inherent ambiguity and limited expressiveness of natural language. To overcome this, we propose the Avatar Concept Slider (ACS), a 3D avatar editing method that allows precise editing of semantic concepts in human avatars towards a specified intermediate point between two extremes of concepts, akin to moving a knob along a slider track. To achieve this, our ACS has three designs: Firstly, a Concept Sliding Loss based on linear discriminant analysis to pinpoint the concept-specific axes for precise editing. Secondly, an Attribute Preserving Loss based on principal component analysis for improved preservation of avatar identity during editing. We further propose a 3D Gaussian Splatting primitive selection mechanism based on concept-sensitivity, which updates only the primitives that are the most sensitive to our target concept, to improve efficiency. Results demonstrate that our ACS enables controllable 3D avatar editing, without compromising the avatar quality or its identifying attributes.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 32 of its 43 references that are in the map. First posted on arXiv 26 Aug 2024.
Builds on
32 of 43 references.
References · 32
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- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
- 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
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- 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,207
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- 2021Image Segmentation Using Text and Image Promptscited by 509
- 2023Instruct-NeRF2NeRF: Editing 3D Scenes with Instructionscited by 482
- 2023GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splattingcited by 331
20 more
- 2023Text-to-3D using Gaussian Splattingcited by 299
- 2023LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generationcited by 258
- 2023GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Modelscited by 255
- 2023Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesiscited by 232
- 2023DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Modelscited by 154
- 2023DreamEditor: Text-Driven 3D Scene Editing with Neural Fieldscited by 154
- 2023Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Modelscited by 148
- 2023Human Gaussian Splatting: Real-time Rendering of Animatable Avatarscited by 105
- 2023DreamHuman: Animatable 3D Avatars from Textcited by 102
- 2023HumanGaussian: Text-Driven 3D Human Generation with Gaussian Splattingcited by 89
- 2023AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Controlcited by 84
- 2023DreamWaltz: Make a Scene with Complex 3D Animatable Avatarscited by 82
- 2023AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Posecited by 60
- 2022ClipFace: Text-guided Editing of Textured 3D Morphable Modelscited by 59
- 2023HeadSculpt: Crafting 3D Head Avatars with Textcited by 48
- 2023Text-Guided Generation and Editing of Compositional 3D Avatarscited by 39
- 2023SCEdit: Efficient and Controllable Image Diffusion Generation via Skip Connection Editingcited by 37
- 2023AvatarStudio: Text-driven Editing of 3D Dynamic Human Head Avatarscited by 29
- 2023AvatarStudio: High-fidelity and Animatable 3D Avatar Creation from Textcited by 16
- 2023HQ3DAvatar: High Quality Controllable 3D Head Avatarcited by 9
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