Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome-Multi-Task-Learning

An up-to-date list of works on Multi-Task Learning
https://github.com/WeiHongLee/Awesome-Multi-Task-Learning

[paper
[paper - Task-Learning-PyTorch)]
[paper
[paper
[paper
[paper
[paper
NYUv2
Cityscapes - dataset.com/)]
PASCAL-Context - context/)]
Taskonomy
KITTI
SUN RGB-D
BDD100K - data.berkeley.edu/)]
Omnidata
[dataset and code
Meta-dataset - research/meta-dataset)]
Visual Domain Decathlon
CelebA
[Multi-Task-Transformer - task Learning including dense prediction problems and 3D detection on Cityscapes.
[Multi-Task-Learning-PyTorch - task Dense Prediction.
[Auto-λ - task Dense Prediction, Robotics.
[UniversalRepresentations - task Dense Prediction](https://github.com/VICO-UoE/UniversalRepresentations/tree/main/DensePred) (including different loss weighting strategies), [Multi-domain Classification](https://github.com/VICO-UoE/UniversalRepresentations/tree/main/VisualDecathlon), [Cross-domain Few-shot Learning](https://github.com/VICO-UoE/URL).
[MTAN - task Dense Prediction, Multi-domain Classification.
[ASTMT - task Dense Prediction.
[LibMTL - task Dense Prediction.
[MTPSL - task Partially-supervised Learning for Dense Prediction.
[Resisual Adapater - domain Classification.
[paper - research/BayesAgg_MTL)]
[paper
[paper
[paper - CVPR-2024)]
[paper
[paper - research/BayesAgg_MTL)]
[paper
[paper - UoE/MTPSL)]
[paper
[paper
[paper - park.github.io/DTR/)]
[paper
[paper
[paper
[paper - research/deeplab2)]
[paper
[paper
[paper
[paper
[paper
[paper
[paper - Model-Selector)]
[paper
[paper - research/google-research/tree/master/moe_mtl)]
[paper
[paper - based-MTL)]
[paper
[paper
[paper
[paper
[paper
[paper - jku/L2M)]
InvPT++ - Task-Transformer/tree/main/InvPT)]
[paper - XIX/FAMO)]
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper - www.cs.umass.edu/mod-squad/)]
[paper - lu/etr-nlp-mtl)]
[paper
[paper
[paper - Task-Transformer/tree/main/TaskPrompter)] [[dataset](https://arxiv.org/pdf/2304.00971.pdf)]
[paper
[paper
[paper
[paper - vision/DenseMTL)]
[paper
[paper
[paper
[paper
[paper - Group/M3ViT)]
[paper
[paper - with-Category-Shifts)]
[paper
[paper
Auto-λ - lambda)]
Universal Representations - UoE/UniversalRepresentations)]
[paper
[paper
[paper
InvPT
MultiMAE
[paper
[paper
[paper
[paper - task-oriented_generative_modeling)]
[paper - mtl)]
[paper
Gato
MTPSL - UoE/MTPSL)]
TSA - UoE/URL)]
OMNIVORE
[paper
[paper - labs.com/~mas/DYMU/)]
SHIFT
[paper - Labs/DiSparse-Multitask-Model-Compression)]
MulT
[paper
[paper
[paper - research/google-research/tree/master/muNet)]
[paper
[paper
[paper - RL/AdaRL-code)]
[paper - parameter-efficient-tuning)]
Rotograd
[paper
[paper
[paper
[paper
[paper
[paper
CAGrad - XIX/CAGrad)]
[paper
[paper
[paper
[paper
[paper
[paper - VILAB/XDEnsembles)]
[paper
URL - UoE/URL)]
tri-M - M-ICCV)]
[paper
[paper
[paper
[paper
FLUTE - research/meta-dataset)]
[paper
[paper
[paper - uda)]
[paper - tasking)]
[paper
[paper
[paper
[paper
[paper
[paper - MTL)]
Gradient Vaccine
IMTL
[paper
URT
[paper
[paper - weighting)]
[paper - Module)]
[paper
GradDrop
PCGrad - PCGrad)]
[paper
[paper
[paper
[paper
[paper
[paper - Task-Learning-PyTorch)]
[paper
[paper
[paper
[paper - repo/duality-diagram-similarity)]
KD4MTL - UoE/KD4MTL)]
[paper
[paper - VILAB/XTConsistency)]
paper - multi-task)]
[paper
[paper
[paper
[paper - gfx/ContinuousParetoMTL)]
[paper
[paper
paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper - L/ParetoMTL)]
[paper
[paper - Paper.pdf)]
Orthogonal
[paper
[paper
[paper - snu/Deep-Elastic-Network)]
[paper - task-architecture-search)]
[paper
[paper - research/google-research/tree/master/bam)]
[paper
[paper - CNN)]
MTAN + DWA
[paper
[paper
[paper - CVPR19-release)]
Geometric Loss Strategy (GLS)
[paper
[paper - n-Pals)]
[paper
[paper
[paper
[paper
[paper - networks)]
[paper
[paper
MGDA - org/MultiObjectiveOptimization)]
[paper - Auxiliary-Losses-Using-Gradient-Similarity)]
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
Uncertainty
[paper
GradNorm
[paper
[paper
[paper
[paper - ros/RoutingNetworks)
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper - wrn)]
[paper
AdaLoss
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
Cross-Stitch - stitch-Networks-for-Multi-task-Learning)]
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
[paper
Universal Representations for Computer Vision Workshop at BMVC 2022
Workshop on Multi-Task Learning in Computer Vision (DeepMTL) at ICCV 2021
Adaptive and Multitask Learning: Algorithms & Systems Workshop (AMTL) at ICML 2019
Workshop on Multi-Task and Lifelong Reinforcement Learning at ICML 2015
Transfer and Multi-Task Learning: Trends and New Perspectives at NeurIPS 2015
Second Workshop on Transfer and Multi-task Learning at NeurIPS 2014
New Directions in Transfer and Multi-Task: Learning Across Domains and Tasks Workshop at NeurIPS 2013
CS 330: Deep Multi-Task and Meta Learning

Programming Languages

Keywords

multi-task-learning 5 computer-vision 2 pytorch 2 pascal 2 scene-understanding 2 segmentation 2 cityscapes 1 cityscapes-3d 1 deep-learning 1 depth-estimation 1 eccv2022 1 human-parsing 1 nyudv2 1 few-shot-learning 1 multi-domain-learning 1 multitask-learning 1 universal-representation 1 partially-supervised 1 semi-supervised-learning 1 eccv2020 1 nyud 1 attention-model 1 auxiliary-learning 1 meta-learning 1