44 citations · 72 across the 7 of their papers we have counts for
8 papers
ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking
Wenshuo Li, Xinghao Chen, Han Shu +2
Large language models (LLM) have recently attracted significant attention in the field of artificial intelligence. However, the training process of these models poses significant c…
TinySAM: Pushing the Envelope for Efficient Segment Anything Model
Han Shu, Wenshuo Li, Yehui Tang +5
Recently segment anything model (SAM) has shown powerful segmentation capability and has drawn great attention in computer vision fields. Massive following works have developed var…
Coarse-to-Fine Searching for Efficient Generative Adversarial Networks
Jiahao Wang, Han Shu, Weihao Xia +2
This paper studies the neural architecture search (NAS) problem for developing efficient generator networks. Compared with deep models for visual recognition tasks, generative adve…
Optical Flow Distillation: Towards Efficient and Stable Video Style Transfer
Xinghao Chen, Yiman Zhang, Yunhe Wang +3
Video style transfer techniques inspire many exciting applications on mobile devices. However, their efficiency and stability are still far from satisfactory. To boost the transfer…
Distilling portable Generative Adversarial Networks for Image Translation
Hanting Chen, Yunhe Wang, Han Shu +5
Despite Generative Adversarial Networks (GANs) have been widely used in various image-to-image translation tasks, they can be hardly applied on mobile devices due to their heavy co…
Automatically Searching for U-Net Image Translator Architecture
Han Shu, Yunhe Wang
Image translators have been successfully applied to many important low level image processing tasks. However, classical network architecture of image translator like U-Net, is borr…