Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

31 January 2024

Papers citing "Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model"

10 / 10 papers shown

Title
Adaptive Blind All-in-One Image Restoration David Serrano-Lozano Luis Herranz Shaolin Su Javier Vázquez-Corral VLM 87 0 0 27 Nov 2024
Low-Rank Interconnected Adaptation Across Layers Yibo Zhong Yao Zhou OffRL MoE 36 1 0 13 Jul 2024
PhysMLE: Generalizable and Priors-Inclusive Multi-task Remote Physiological Measurement Jiyao Wang Hao Lu Ange Wang Xiao Yang Ying Chen Dengbo He Kaishun Wu 16 3 0 10 May 2024
Customized Segment Anything Model for Medical Image Segmentation Kaiwen Zhang Dong Liu MedIm VLM 95 276 0 26 Apr 2023
Mixture-of-Experts with Expert Choice Routing Yan-Quan Zhou Tao Lei Han-Chu Liu Nan Du Yanping Huang Vincent Zhao Andrew M. Dai Zhifeng Chen Quoc V. Le James Laudon MoE 137 323 0 18 Feb 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 255 7,337 0 11 Nov 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 275 3,784 0 18 Apr 2021
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions Wenhai Wang Enze Xie Xiang Li Deng-Ping Fan Kaitao Song Ding Liang Tong Lu Ping Luo Ling Shao ViT 263 3,538 0 24 Feb 2021
TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation Yundong Zhang Huiye Liu Qiang Hu ViT MedIm 192 869 0 16 Feb 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 229 74,467 0 18 May 2015