Minimalist and High-Performance Semantic Segmentation with Plain Vision
Transformers

Minimalist and High-Performance Semantic Segmentation with Plain Vision Transformers

19 October 2023

Papers citing "Minimalist and High-Performance Semantic Segmentation with Plain Vision Transformers"

9 / 9 papers shown

Title
CIT: Rethinking Class-incremental Semantic Segmentation with a Class Independent Transformation Jinchao Ge Bowen Zhang Akide Liu Minh Hieu Phan Qi Chen Yangyang Shu Yang Zhao VLM CLL 25 0 0 05 Nov 2024
ComFe: An Interpretable Head for Vision Transformers Evelyn J. Mannix H. Bondell Howard Bondell VLM ViT 21 1 0 07 Mar 2024
Win-Win: Training High-Resolution Vision Transformers from Two Windows Vincent Leroy Jérôme Revaud Thomas Lucas Philippe Weinzaepfel ViT 27 2 0 01 Oct 2023
When Multi-Task Learning Meets Partial Supervision: A Computer Vision Review Maxime Fontana Michael W. Spratling Miaojing Shi 28 5 0 25 Jul 2023
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
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
Deep High-Resolution Representation Learning for Visual Recognition Jingdong Wang Ke Sun Tianheng Cheng Borui Jiang Chaorui Deng ... Yadong Mu Mingkui Tan Xinggang Wang Wenyu Liu Bin Xiao 190 3,480 0 20 Aug 2019
Feature Pyramid Networks for Object Detection Tsung-Yi Lin Piotr Dollár Ross B. Girshick Kaiming He Bharath Hariharan Serge J. Belongie ObjD 166 21,643 0 09 Dec 2016
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 420 15,438 0 02 Nov 2015