Reparameterizing Convolutions for Incremental Multi-Task Learning
without Task Interference

Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference

24 July 2020

Menelaos Kanakis

David Brüggemann

Stamatios Georgoulis

Luc Van Gool

Papers citing "Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference"

10 / 10 papers shown

Title
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning Yuxiang Lu Shengcao Cao Yu-xiong Wang 45 1 0 18 Oct 2024
SGW-based Multi-Task Learning in Vision Tasks Ruiyuan Zhang Yuyao Chen Yuchi Huo Jiaxiang Liu Dianbing Xi Jie Liu Chao Wu 26 0 0 03 Oct 2024
Composite Learning for Robust and Effective Dense Predictions Menelaos Kanakis Thomas E. Huang David Brüggemann F. I. F. Richard Yu Luc Van Gool SSL 32 3 0 13 Oct 2022
Curbing Task Interference using Representation Similarity-Guided Multi-Task Feature Sharing Naresh Gurulingan Elahe Arani Bahram Zonooz 16 1 0 19 Aug 2022
E2-AEN: End-to-End Incremental Learning with Adaptively Expandable Network Guimei Cao Zhanzhan Cheng Yunlu Xu Duo Li Shiliang Pu Yi Niu Fei Wu CLL 15 2 0 14 Jul 2022
Factorizing Knowledge in Neural Networks Xingyi Yang Jingwen Ye Xinchao Wang MoMe 28 121 0 04 Jul 2022
Multi-Task Learning with Multi-Query Transformer for Dense Prediction Yangyang Xu Xiangtai Li Haobo Yuan Yibo Yang Lefei Zhang ViT 15 45 0 28 May 2022
Representation Compensation Networks for Continual Semantic Segmentation Chang-Bin Zhang Jianqiang Xiao Xialei Liu Ying-Cong Chen Mingg-Ming Cheng SSeg CLL 32 93 0 10 Mar 2022
Multi-Domain Incremental Learning for Semantic Segmentation Prachi Garg Rohit Saluja V. Balasubramanian Chetan Arora A. Subramanian C. V. Jawahar CLL 25 32 0 23 Oct 2021
Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation Suman Saha Anton Obukhov D. Paudel Menelaos Kanakis Yuhua Chen Stamatios Georgoulis Luc Van Gool OOD 25 55 0 17 May 2021