DeepAI AI Chat
Log In Sign Up

Domain Generalization by Solving Jigsaw Puzzles

by   Fabio Maria Carlucci, et al.
HUAWEI Technologies Co., Ltd.
Istituto Italiano di Tecnologia
Politecnico di Torino

Human adaptability relies crucially on the ability to learn and merge knowledge both from supervised and unsupervised learning: the parents point out few important concepts, but then the children fill in the gaps on their own. This is particularly effective, because supervised learning can never be exhaustive and thus learning autonomously allows to discover invariances and regularities that help to generalize. In this paper we propose to apply a similar approach to the task of object recognition across domains: our model learns the semantic labels in a supervised fashion, and broadens its understanding of the data by learning from self-supervised signals how to solve a jigsaw puzzle on the same images. This secondary task helps the network to learn the concepts of spatial correlation while acting as a regularizer for the classification task. Multiple experiments on the PACS, VLCS, Office-Home and digits datasets confirm our intuition and show that this simple method outperforms previous domain generalization and adaptation solutions. An ablation study further illustrates the inner workings of our approach.


page 3

page 8


Self-Supervised Learning Across Domains

Human adaptability relies crucially on learning and merging knowledge fr...

Self-supervised Regularization for Text Classification

Text classification is a widely studied problem and has broad applicatio...

Self-Supervised Representation Learning for Detection of ACL Tear Injury in Knee MRI

The success and efficiency of Deep Learning based models for computer vi...

Self-supervised Visual Attribute Learning for Fashion Compatibility

Many self-supervised learning (SSL) methods have been successful in lear...

Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization

The generalization capability of neural networks across domains is cruci...

Learning to Generalize One Sample at a Time with Self-Supervision

Although deep networks have significantly increased the performance of v...

Towards Shape Biased Unsupervised Representation Learning for Domain Generalization

It is known that, without awareness of the process, our brain appears to...