11 citations · 24 across the 15 of their papers we have counts for
15 papers
United we stand, Divided we fall: Handling Weak Complementary Relationships for Audio-Visual Emotion Recognition in Valence-Arousal Space
R. Gnana Praveen, Jahangir Alam, Eric Charton
Audio and visual modalities are two predominant contact-free channels in videos, which are often expected to carry a complementary relationship with each other. However, they may n…
Inconsistency-Aware Cross-Attention for Audio-Visual Fusion in Dimensional Emotion Recognition
G Rajasekhar, Jahangir Alam
Leveraging complementary relationships across modalities has recently drawn a lot of attention in multimodal emotion recognition. Most of the existing approaches explored cross-att…
Audio-Visual Person Verification based on Recursive Fusion of Joint Cross-Attention
R. Gnana Praveen, Jahangir Alam
Person or identity verification has been recently gaining a lot of attention using audio-visual fusion as faces and voices share close associations with each other. Conventional ap…
Dynamic Cross Attention for Audio-Visual Person Verification
R. Gnana Praveen, Jahangir Alam
Although person or identity verification has been predominantly explored using individual modalities such as face and voice, audio-visual fusion has recently shown immense potentia…
Recursive Joint Cross-Modal Attention for Multimodal Fusion in Dimensional Emotion Recognition
R. Gnana Praveen, Jahangir Alam
Though multimodal emotion recognition has achieved significant progress over recent years, the potential of rich synergic relationships across the modalities is not fully exploited…
Cross-Attention is Not Always Needed: Dynamic Cross-Attention for Audio-Visual Dimensional Emotion Recognition
R. Gnana Praveen, Jahangir Alam
In video-based emotion recognition, audio and visual modalities are often expected to have a complementary relationship, which is widely explored using cross-attention. However, th…
Audio-Visual Speaker Verification via Joint Cross-Attention
R. Gnana Praveen, Jahangir Alam
Speaker verification has been widely explored using speech signals, which has shown significant improvement using deep models. Recently, there has been a surge in exploring faces a…
Recursive Joint Attention for Audio-Visual Fusion in Regression based Emotion Recognition
R Gnana Praveen, Eric Granger, Patrick Cardinal
In video-based emotion recognition (ER), it is important to effectively leverage the complementary relationship among audio (A) and visual (V) modalities, while retaining the intra…
Audio-Visual Fusion for Emotion Recognition in the Valence-Arousal Space Using Joint Cross-Attention
R Gnana Praveen, Eric Granger, Patrick Cardinal
Automatic emotion recognition (ER) has recently gained lot of interest due to its potential in many real-world applications. In this context, multimodal approaches have been shown…
A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition
R. Gnana Praveen, Wheidima Carneiro de Melo, Nasib Ullah +8
Multimodal emotion recognition has recently gained much attention since it can leverage diverse and complementary relationships over multiple modalities (e.g., audio, visual, biosi…
Cross Attentional Audio-Visual Fusion for Dimensional Emotion Recognition
R. Gnana Praveen, Eric Granger, Patrick Cardinal
Multimodal analysis has recently drawn much interest in affective computing, since it can improve the overall accuracy of emotion recognition over isolated uni-modal approaches. Th…
Holistic Guidance for Occluded Person Re-Identification
Madhu Kiran, R Gnana Praveen, Le Thanh Nguyen-Meidine +3
In real-world video surveillance applications, person re-identification (ReID) suffers from the effects of occlusions and detection errors. Despite recent advances, occlusions cont…
Weakly Supervised Learning for Facial Affective Behavior Analysis : A Review
R. Gnana Praveen, Patrick Cardinal, Eric Granger
Recent advances in deep learning (DL) and computational capacity have enabled facial affective behavior analysis (FABA) to progress from static images captured in controlled settin…
Deep Domain Adaptation for Ordinal Regression of Pain Intensity Estimation Using Weakly-Labelled Videos
R. Gnana Praveen, Eric Granger, Patrick Cardinal
Estimation of pain intensity from facial expressions captured in videos has an immense potential for health care applications. Given the challenges related to subjective variations…
Deep Weakly-Supervised Domain Adaptation for Pain Localization in Videos
R. Gnana Praveen, Eric Granger, Patrick Cardinal
Automatic pain assessment has an important potential diagnostic value for populations that are incapable of articulating their pain experiences. As one of the dominating nonverbal…