4 papers · 1 filter
Deep Semi-supervised Learning with Double-Contrast of Features and Semantics
Quan Feng, Jiayu Yao, Zhison Pan +1
In recent years, the field of intelligent transportation systems (ITS) has achieved remarkable success, which is mainly due to the large amount of available annotation data. Howeve…
Learning Downstream Task by Selectively Capturing Complementary Knowledge from Multiple Self-supervisedly Learning Pretexts
Jiayu Yao, Qingyuan Wu, Quan Feng +1
Self-supervised learning (SSL), as a newly emerging unsupervised representation learning paradigm, generally follows a two-stage learning pipeline: 1) learning invariant and discri…
Learning Multi-Tasks with Inconsistent Labels by using Auxiliary Big Task
Quan Feng, Songcan Chen
Multi-task learning is to improve the performance of the model by transferring and exploiting common knowledge among tasks. Existing MTL works mainly focus on the scenario where la…
Learning Twofold Heterogeneous Multi-Task by Sharing Similar Convolution Kernel Pairs
Quan Feng, Songcan Chen
Heterogeneous multi-task learning (HMTL) is an important topic in multi-task learning (MTL). Most existing HMTL methods usually solve either scenario where all tasks reside in the…