Text2Sign: A Single-GPU Diffusion Baseline for Text-to-Sign Language Video Generation
Sign language is a primary communication channel for millions of Deaf and hard-of-hearing people, yet text-to-signer video generation remains costly because video diffusion models are expensive to train and evaluate. This paper presents Text2Sign, a text-conditioned diffusion model for short sign-language clips that runs on a single NVIDIA L4 GPU. It combines a frozen vision-language text encoder with a 3D encoder-decoder and factorized spatiotemporal attention to reduce the cost of full-video attention while preserving motion coherence. We compare convolution-only and transformer-style backbones, frozen pretrained and task-specific text encoders, and factorized versus full attention. On ...
| Authors | Ruize Xia |
|---|---|
| Primary category | cs.CL |
| Published | 14 July 2026 |
| Last updated at source | 14 July 2026 |
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