Search Results for author: Fangmin Chen

Found 3 papers, 2 papers with code

SparseByteNN: A Novel Mobile Inference Acceleration Framework Based on Fine-Grained Group Sparsity

no code implementations30 Oct 2023 Haitao Xu, Songwei Liu, Yuyang Xu, Shuai Wang, Jiashi Li, Chenqian Yan, Liangqiang Li, Lean Fu, Xin Pan, Fangmin Chen

Our framework consists of two parts: (a) A fine-grained kernel sparsity schema with a sparsity granularity between structured pruning and unstructured pruning.

Network Pruning

Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-Resolution

1 code implementation5 Aug 2023 Yong liu, Hang Dong, Boyang Liang, Songwei Liu, Qingji Dong, Kai Chen, Fangmin Chen, Lean Fu, Fei Wang

Since the high resolution of intermediate features in SISR models increases memory and computational requirements, efficient SISR transformers are more favored.

Image Super-Resolution

Residual Local Feature Network for Efficient Super-Resolution

1 code implementation16 May 2022 Fangyuan Kong, Mingxi Li, Songwei Liu, Ding Liu, Jingwen He, Yang Bai, Fangmin Chen, Lean Fu

Moreover, we revisit the popular contrastive loss and observe that the selection of intermediate features of its feature extractor has great influence on the performance.

Image Super-Resolution SSIM

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