research
∙
07/06/2023
Active Learning with Contrastive Pre-training for Facial Expression Recognition
Deep learning has played a significant role in the success of facial exp...
research
∙
06/02/2023
Exploring the Boundaries of Semi-Supervised Facial Expression Recognition: Learning from In-Distribution, Out-of-Distribution, and Unconstrained Data
Deep learning-based methods have been the key driving force behind much ...
research
∙
06/02/2023
Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data
We propose UnMixMatch, a semi-supervised learning framework which can le...
research
∙
06/01/2023
Consistency-guided Prompt Learning for Vision-Language Models
We propose Consistency-guided Prompt learning (CoPrompt), a new fine-tun...
research
∙
11/27/2022
Impact of Labelled Set Selection and Supervision Policies on Semi-supervised Learning
In semi-supervised representation learning frameworks, when the number o...
research
∙
09/02/2022
Temporal Contrastive Learning with Curriculum
We present ConCur, a contrastive video representation learning method th...
research
∙
07/31/2022
Analysis of Semi-Supervised Methods for Facial Expression Recognition
Training deep neural networks for image recognition often requires large...
research
∙
08/15/2021
Self-supervised Contrastive Learning of Multi-view Facial Expressions
Facial expression recognition (FER) has emerged as an important componen...
research
∙
08/06/2021