# Information-Regularized Constrained Inversion for Stable Avatar Editing from Sparse Supervision

arXiv: https://arxiv.org/abs/2604.02883 · HTML: https://mlsanity.com/paper/2604.02883/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 32 of its 36 references that are in the map.
- First posted on arXiv 3 Apr 2026.

## Builds on (most cited first, 30 of 32)

- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans](https://mlsanity.com/paper/2012.15838/) (2020)
- [Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions](https://mlsanity.com/paper/2303.12789/) (2023)
- [NeuMan: Neural Human Radiance Field from a Single Video](https://mlsanity.com/paper/2203.12575/) (2022)
- [3DGS-Avatar: Animatable Avatars via Deformable 3D Gaussian Splatting](https://mlsanity.com/paper/2312.09228/) (2023)
- [GaussianEditor: Editing 3D Gaussians Delicately with Text Instructions](https://mlsanity.com/paper/2311.16037/) (2023)
- [GauHuman: Articulated Gaussian Splatting from Monocular Human Videos](https://mlsanity.com/paper/2312.02973/) (2023)
- [InstantAvatar: Learning Avatars from Monocular Video in 60 Seconds](https://mlsanity.com/paper/2212.10550/) (2022)
- [ActiveNeRF: Learning where to See with Uncertainty Estimation](https://mlsanity.com/paper/2209.08546/) (2022)
- [Human Gaussian Splatting: Real-time Rendering of Animatable Avatars](https://mlsanity.com/paper/2311.17113/) (2023)
- [DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editing](https://mlsanity.com/paper/2404.18929/) (2024)
- [ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fields](https://mlsanity.com/paper/2402.00864/) (2024)
- [FisherRF: Active View Selection and Uncertainty Quantification for Radiance Fields using Fisher Information](https://mlsanity.com/paper/2311.17874/) (2023)
- [IDOL: Instant Photorealistic 3D Human Creation from a Single Image](https://mlsanity.com/paper/2412.14963/) (2024)
- [Reconstructing 3D Human Pose by Watching Humans in the Mirror](https://mlsanity.com/paper/2104.00340/) (2021)
- [EditSplat: Multi-View Fusion and Attention-Guided Optimization for View-Consistent 3D Scene Editing with 3D Gaussian Splatting](https://mlsanity.com/paper/2412.11520/) (2024)
- [GSEdit: Efficient Text-Guided Editing of 3D Objects via Gaussian Splatting](https://mlsanity.com/paper/2403.05154/) (2024)
- [LayGA: Layered Gaussian Avatars for Animatable Clothing Transfer](https://mlsanity.com/paper/2405.07319/) (2024)
- [GaussianVTON: 3D Human Virtual Try-ON via Multi-Stage Gaussian Splatting Editing with Image Prompting](https://mlsanity.com/paper/2405.07472/) (2024)
- [InterGSEdit: Interactive 3D Gaussian Splatting Editing with 3D Geometry-Consistent Attention Prior](https://mlsanity.com/paper/2507.04961/) (2025)
- [POp-GS: Next Best View in 3D-Gaussian Splatting with P-Optimality](https://mlsanity.com/paper/2503.07819/) (2025)
- [Disco4D: Disentangled 4D Human Generation and Animation from a Single Image](https://mlsanity.com/paper/2409.17280/) (2024)
- [GS-VTON: Controllable 3D Virtual Try-on with Gaussian Splatting](https://mlsanity.com/paper/2410.05259/) (2024)
- [Tinker: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene Optimization](https://mlsanity.com/paper/2508.14811/) (2025)
- [MoGA: 3D Generative Avatar Prior for Monocular Gaussian Avatar Reconstruction](https://mlsanity.com/paper/2507.23597/) (2025)
- [LAGA: Layered 3D Avatar Generation and Customization via Gaussian Splatting](https://mlsanity.com/paper/2405.12663/) (2024)
- [SplatPainter: Interactive Authoring of 3D Gaussians from 2D Edits via Test-Time Training](https://mlsanity.com/paper/2512.05354/) (2025)
- [TeRA: Rethinking Text-guided Realistic 3D Avatar Generation](https://mlsanity.com/paper/2509.02466/) (2025)
- [EditCast3D: Single-Frame-Guided 3D Editing with Video Propagation and View Selection](https://mlsanity.com/paper/2510.13652/) (2025)
- [GGAvatar: Reconstructing Garment-Separated 3D Gaussian Splatting Avatars from Monocular Video](https://mlsanity.com/paper/2411.09952/) (2024)

## Abstract (arXiv)

Editing animatable human avatars typically relies on sparse supervision, often a few edited keyframes, yet naively fitting a reconstructed avatar to these edits frequently causes identity leakage and pose-dependent temporal flicker. We argue that these failures are best understood as an ill-conditioned inversion: the available edited constraints do not sufficiently determine the latent directions responsible for the intended edit. We propose a conditioning-guided edited reconstruction framework that performs editing as a constrained inversion in a structured avatar latent space, restricting updates to a low-dimensional, part-specific edit subspace to prevent unintended identity changes. Crucially, we design the editing constraints during inversion by optimizing a conditioning objective derived from a local linearization of the full decoding-and-rendering pipeline, yielding an edit-subspace information matrix whose spectrum predicts stability and drives frame reweighting / keyframe activation. The resulting method operates on small subspace matrices and can be implemented efficiently (e.g., via Hessian-vector products), and improves stability under limited edited supervision.