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GeReA: Question-Aware Prompt Captions for Knowledge-based Visual Question Answering
Therefore, we propose GeReA, a generate-reason framework that prompts a MLLM like InstructBLIP with question relevant vision and language information to generate knowledge-relevant descriptions and reasons those descriptions for knowledge-based VQA.
LOGO-Former: Local-Global Spatio-Temporal Transformer for Dynamic Facial Expression Recognition
Previous methods for dynamic facial expression recognition (DFER) in the wild are mainly based on Convolutional Neural Networks (CNNs), whose local operations ignore the long-range dependencies in videos.
Dynamic Facial Expression Recognition
Facial Expression Recognition
Spatio-Temporal Transformer for Dynamic Facial Expression Recognition in the Wild
Previous methods for dynamic facial expression in the wild are mainly based on Convolutional Neural Networks (CNNs), whose local operations ignore the long-range dependencies in videos.
Ranked #5 on
Dynamic Facial Expression Recognition
on FERV39k
Dynamic Facial Expression Recognition
Facial Expression Recognition
+1
Hybrid Mutimodal Fusion for Dimensional Emotion Recognition
For the MuSe-Stress sub-challenge, we highlight our solutions in three aspects: 1) the audio-visual features and the bio-signal features are used for emotional state recognition.
Facial Expression Recognition with Visual Transformers and Attentional Selective Fusion
Facial Expression Recognition (FER) in the wild is extremely challenging due to occlusions, variant head poses, face deformation and motion blur under unconstrained conditions.
Facial Expression Recognition
Facial Expression Recognition (FER)
