ViM: Vision Middleware for Unified Downstream Transferring

ViM: Vision Middleware for Unified Downstream Transferring

13 March 2023

Jingren Zhou

Papers citing "ViM: Vision Middleware for Unified Downstream Transferring"

9 / 9 papers shown

Title
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition Shoufa Chen Chongjian Ge Zhan Tong Jiangliu Wang Yibing Song Jue Wang Ping Luo 141 631 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 258 7,337 0 11 Nov 2021
Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling Renrui Zhang Rongyao Fang Wei Zhang Peng Gao Kunchang Li Jifeng Dai Yu Qiao Hongsheng Li VLM 184 384 0 06 Nov 2021
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 236 780 0 14 Oct 2021
ImageNet-21K Pretraining for the Masses T. Ridnik Emanuel Ben-Baruch Asaf Noy Lihi Zelnik-Manor SSeg VLM CLIP 154 676 0 22 Apr 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 278 3,784 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,898 0 31 Dec 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 238 3,029 0 09 Mar 2020
CrowdHuman: A Benchmark for Detecting Human in a Crowd Shuai Shao Zijian Zhao Boxun Li Tete Xiao Gang Yu Xiangyu Zhang Jian-jun Sun 205 670 0 30 Apr 2018