SMMix: Self-Motivated Image Mixing for Vision Transformers

26 December 2022

Papers citing "SMMix: Self-Motivated Image Mixing for Vision Transformers"

8 / 8 papers shown

Title
Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection M. L. Mekhalfi Davide Boscaini Fabio Poiesi 25 6 0 29 Aug 2023
Harnessing Hard Mixed Samples with Decoupled Regularizer Zicheng Liu Siyuan Li Ge Wang Cheng Tan Lirong Wu Stan Z. Li 39 17 0 21 Mar 2022
Imperceptible Adversarial Examples for Fake Image Detection Quanyu Liao Yuezun Li Xiaoqiang Guo Bin Kong Yingxin Zhu Jianlei Liu Zhuqing Jiang Qi Song Xi Wu AAML 82 33 0 03 Jun 2021
Visformer: The Vision-friendly Transformer Zhengsu Chen Lingxi Xie Jianwei Niu Xuefeng Liu Longhui Wei Qi Tian ViT 109 206 0 26 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
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 220 510 0 11 Feb 2021
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity Jang-Hyun Kim Wonho Choo Hosan Jeong Hyun Oh Song 195 173 0 05 Feb 2021
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels Sangdoo Yun Seong Joon Oh Byeongho Heo Dongyoon Han Junsuk Choe Sanghyuk Chun 384 139 0 13 Jan 2021