Sparse-Tuning: Adapting Vision Transformers with Efficient Fine-tuning
and Inference

Sparse-Tuning: Adapting Vision Transformers with Efficient Fine-tuning and Inference

23 May 2024

Zunnan Xu

Siteng Huang

Papers citing "Sparse-Tuning: Adapting Vision Transformers with Efficient Fine-tuning and Inference"

8 / 8 papers shown

Title
MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression Comprehension Ting Liu Zunnan Xu Yue Hu Liangtao Shi Zhiqiang Wang Quanjun Yin 54 2 0 03 Jan 2025
Time-, Memory- and Parameter-Efficient Visual Adaptation Otniel-Bogdan Mercea Alexey Gritsenko Cordelia Schmid Anurag Arnab VLM 27 13 0 05 Feb 2024
VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understanding Yi Xin Junlong Du Qiang Wang Zhiwen Lin Ke Yan VPVLM 70 47 0 14 Dec 2023
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition Shoufa Chen Chongjian Ge Zhan Tong Jiangliu Wang Yibing Song Jue Wang Ping Luo 138 631 0 26 May 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
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 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
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 236 35,884 0 25 Aug 2016