# InstructHumans: Editing Animated 3D Human Textures with Instructions Source: [InstructHumans: Editing Animated 3D Human Textures with Instructions]() Collection index: [llms.txt]() Data updated: 2026-03-07T05:00:10.880Z Authors: Jiayin Zhu, Linlin Yang, Angela Yao Published: 2024-04-05T11:45:03.000Z ## Abstract We present InstructHumans, a novel framework for instruction-driven {animatable} 3D human texture editing. Existing text-based 3D editing methods often directly apply Score Distillation Sampling (SDS). SDS, designed for generation tasks, cannot account for the defining requirement of editing -- maintaining consistency with the source avatar. This work shows that naively using SDS harms editing, as it may destroy consistency. We propose a modified SDS for Editing (SDS-E) that selectively incorporates subterms of SDS across diffusion timesteps. We further enhance SDS-E with spatial smoothness regularization and gradient-based viewpoint sampling for edits with sharp and high-fidelity detailing. Incorporating SDS-E into a 3D human texture editing framework allows us to outperform existing 3D editing methods. Our avatars faithfully reflect the textual edits while remaining consistent with the original avatars. Project page: https://jyzhu.top/instruct-humans/. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Human Avatar Texture Editing on User Study 10 full-body and 3 localized human avatar edits](): Human Avatar Texture Editing; User Study 10 full-body and 3 localized human avatar edits; Visual Quality: 57.82. ## Original sources and implementation [Original paper]() [PDF]()