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Found 8 papers, 1 papers with code
LD-Pruner: Efficient Pruning of Latent Diffusion Models using Task-Agnostic Insights
Latent Diffusion Models (LDMs) have emerged as powerful generative models, known for delivering remarkable results under constrained computational resources.
EdgeFusion: On-Device Text-to-Image Generation
The intensive computational burden of Stable Diffusion (SD) for text-to-image generation poses a significant hurdle for its practical application.
LatentSwap: An Efficient Latent Code Mapping Framework for Face Swapping
We show that our framework is applicable to other generators such as StyleNeRF, paving a way to 3D-aware face swapping and is also compatible with other downstream StyleGAN2 generator tasks.
Shortened LLaMA: A Simple Depth Pruning for Large Language Models
Structured pruning of modern large language models (LLMs) has emerged as a way of decreasing their high computational needs.
BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion
Text-to-image (T2I) generation with Stable Diffusion models (SDMs) involves high computing demands due to billion-scale parameters.
DreamBooth Personalized Generation
Image-to-Image Translation
A Unified Compression Framework for Efficient Speech-Driven Talking-Face Generation
Virtual humans have gained considerable attention in numerous industries, e. g., entertainment and e-commerce.
Talking Face Generation with Multilingual TTS
In this work, we propose a joint system combining a talking face generation system with a text-to-speech system that can generate multilingual talking face videos from only the text input.
Deep User Identification Model with Multiple Biometrics
Most research has only focused on single modality or a single task, while the combination of input modality or tasks is yet to be investigated.
