Leveraging the Power of Data Augmentation for Transformer-based Tracking

Leveraging the Power of Data Augmentation for Transformer-based Tracking

15 September 2023

Huchuan Lu

Papers citing "Leveraging the Power of Data Augmentation for Transformer-based Tracking"

7 / 7 papers shown

Title
Transforming Model Prediction for Tracking Christoph Mayer Martin Danelljan Goutam Bhat M. Paul D. Paudel F. I. F. Richard Yu Luc Van Gool 57 160 0 21 Mar 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
Intriguing Properties of Vision Transformers Muzammal Naseer Kanchana Ranasinghe Salman Khan Munawar Hayat F. Khan Ming-Hsuan Yang ViT 248 618 0 21 May 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
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation Golnaz Ghiasi Yin Cui A. Srinivas Rui Qian Tsung-Yi Lin E. D. Cubuk Quoc V. Le Barret Zoph ISeg 223 962 0 13 Dec 2020
Siamese Box Adaptive Network for Visual Tracking Zedu Chen Bineng Zhong Guorong Li Shengping Zhang Rongrong Ji 86 659 0 15 Mar 2020
TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild Matthias Muller Adel Bibi Silvio Giancola Salman Al-Subaihi Bernard Ghanem 203 785 0 28 Mar 2018