May 10, 2022 · We propose the spatio-temporal Transformer (STT) to capture discriminative features within each frame and model contextual relationships among frames.
The local-global spatio-temporal Transformer (LOGO-Former) is proposed to capture discriminative features within each frame and model contextual relationships ...
The spatio-temporal Transformer (STT) is proposed to capture discriminative features within each frame and model contextual relationships among frames to ...
Experiments on two in-the-wild dynamic facial expression datasets (i.e., DFEW and AFEW) indicate that our method provides an effective way to make use of the ...
The quantitative results and the visualization results demonstrate the effectiveness of our method for in-the-wild dynamic facial expression recognition. 2. THE ...
Apr 12, 2024 · We propose a Multi-Scale Spatio-temporal CNN-Transformer network (MSSTNet). Our approach takes spatial features of different scales extracted by CNN and feeds ...
Intensity-Aware Loss for Dynamic Facial Expression Recognition in the Wild ... 66.65, 54.58. Spatio-Temporal Transformer for Dynamic Facial Expression Recognition ...
Its goal is to classify a facial video clip, rather than a still image, into one of the basic emotions. The field of DFER has attracted considerable ...
We propose an enhanced spatial–temporal learning network (ESTLNet) for more robust dynamic facial expression recognition.
This paper proposes a dynamic facial expression recognition transformer (Former-DFER) for the in-the-wild scenario.
Missing: Spatio- | Show results with:Spatio-