Win-Win: Training High-Resolution Vision Transformers from Two Windows

1 October 2023

Papers citing "Win-Win: Training High-Resolution Vision Transformers from Two Windows"

8 / 8 papers shown

Title
Pow3R: Empowering Unconstrained 3D Reconstruction with Camera and Scene Priors Wonbong Jang Philippe Weinzaepfel Vincent Leroy Lourdes Agapito Jérôme Revaud 46 0 0 21 Mar 2025
SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flow Yihan Wang Lahav Lipson Jia Deng 32 36 0 23 May 2024
Masked Image Modeling with Local Multi-Scale Reconstruction Haoqing Wang Yehui Tang Yunhe Wang Jianyuan Guo Zhiwei Deng Kai Han 56 45 0 09 Mar 2023
Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo Lukas Mehl Jenny Schmalfuss Azin Jahedi Yaroslava Nalivayko Andrés Bruhn VGen 23 56 0 03 Mar 2023
GroupViT: Semantic Segmentation Emerges from Text Supervision Jiarui Xu Shalini De Mello Sifei Liu Wonmin Byeon Thomas Breuel Jan Kautz X. Wang ViT VLM 175 494 0 22 Feb 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
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
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