Pith. sign in

REVIEW 1 cited by

Towards Better Adversarial Synthesis of Human Images from Text

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2107.01869 v1 pith:Z7L4BFFU submitted 2021-07-05 cs.CV

Rania Briq , Pratika Kochar , Juergen Gall This is my paper · ORCID
classification cs.CV
keywords humanmodelshapestextindividualsinteractionsmeshessynthesis
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original 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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. CoT-Pose: Chain-of-Thought Reasoning for 3D Pose Generation from Abstract Prompts

    cs.CV 2025-08 reject novelty 6.0 of 10

    CoT-Pose fine-tunes UniPose so that an abstract action phrase is expanded into a detailed pose description, which is then decoded into a 3D SMPL pose.

Pith tools