# Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild

arXiv: https://arxiv.org/abs/2007.15068 · HTML: https://mlsanity.com/paper/2007.15068/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jul 2020.

## Built on by (most cited first, 6 of 6)

- [Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency](https://mlsanity.com/paper/2110.05458/) (2021)
- [TemporalUV: Capturing Loose Clothing with Temporally Coherent UV Coordinates](https://mlsanity.com/paper/2204.03671/) (2022)
- [Total Selfie: Generating Full-Body Selfies](https://mlsanity.com/paper/2308.14740/) (2023)
- [Render In-between: Motion Guided Video Synthesis for Action Interpolation](https://mlsanity.com/paper/2111.01029/) (2021)
- [Direct Dense Pose Estimation](https://mlsanity.com/paper/2204.01263/) (2022)
- [Generating Fit Check Videos with a Handheld Camera](https://mlsanity.com/paper/2505.23886/) (2025)

## Abstract (arXiv)

Due to the ubiquity of smartphones, it is popular to take photos of one's self, or "selfies." Such photos are convenient to take, because they do not require specialized equipment or a third-party photographer. However, in selfies, constraints such as human arm length often make the body pose look unnatural. To address this issue, we introduce textitunselfie, a novel photographic transformation that automatically translates a selfie into a neutral-pose portrait. To achieve this, we first collect an unpaired dataset, and introduce a way to synthesize paired training data for self-supervised learning. Then, to textitunselfie a photo, we propose a new three-stage pipeline, where we first find a target neutral pose, inpaint the body texture, and finally refine and composite the person on the background. To obtain a suitable target neutral pose, we propose a novel nearest pose search module that makes the reposing task easier and enables the generation of multiple neutral-pose results among which users can choose the best one they like. Qualitative and quantitative evaluations show the superiority of our pipeline over alternatives.