Avatar Concept Slider: Controllable Editing of Concepts in 3D Human Avatars

TL;DR

The paper introduces the Avatar Concept Slider (ACS), a novel 3D avatar editing method that allows precise, controllable semantic concept adjustments while preserving avatar identity and improving editing efficiency.

Contribution

The paper presents ACS with concept sliding loss, attribute preserving loss, and a primitive selection mechanism for efficient, precise, and identity-preserving 3D avatar editing.

Findings

Enables controllable semantic editing of 3D avatars.

Preserves avatar identity during editing.

Improves editing efficiency through primitive selection.

Abstract

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.