# Towards Better Adversarial Synthesis of Human Images from Text

Source: [Towards Better Adversarial Synthesis of Human Images from Text](<https://www.sota2.com/research/paper/68fa6a5a1e209131cea27a9f>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:08:37.319Z

Authors: Rania Briq, Pratika Kochar, Juergen Gall

Published: 2021-07-05T08:47:51.000Z

## Abstract

This paper proposes an approach that generates multiple 3D human meshes from text. The human shapes are represented by 3D meshes based on the SMPL model. The model's performance is evaluated on the COCO dataset, which contains challenging human shapes and intricate interactions between individuals. The model is able to capture the dynamics of the scene and the interactions between individuals based on text. We further show how using such a shape as input to image synthesis frameworks helps to constrain the network to synthesize humans with realistic human shapes.

## 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.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2107.01869>)

[PDF](<https://arxiv.org/pdf/2107.01869.pdf>)