A Survey of Resource-efficient LLM and Multimodal Foundation Models

1 code implementation • 16 Jan 2024 • Mengwei Xu, Wangsong Yin, Dongqi Cai, Rongjie Yi, Daliang Xu, QiPeng Wang, Bingyang Wu, Yihao Zhao, Chen Yang, Shihe Wang, Qiyang Zhang, Zhenyan Lu, Li Zhang, Shangguang Wang, Yuanchun Li, Yunxin Liu, Xin Jin, Xuanzhe Liu

Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment.

Unpaired Image-to-Image Translation using Adversarial Consistency Loss

3 code implementations • ECCV 2020 • Yihao Zhao, Ruihai Wu, Hao Dong

Cycle-consistency loss is a widely used constraint for such problems.

Image-to-Image Translation Translation

DLGAN: Disentangling Label-Specific Fine-Grained Features for Image Manipulation

1 code implementation • 22 Nov 2019 • Guanqi Zhan, Yihao Zhao, Bingchan Zhao, Haoqi Yuan, Baoquan Chen, Hao Dong

By mapping the discrete label-specific attribute features into a continuous prior distribution, we leverage the advantages of both discrete labels and reference images to achieve image manipulation in a hybrid fashion.

Attribute Image Manipulation +1