Papers › Continuous Emotion Recognition with Audio-visual Leader-follower Attentive Fusion
Continuous Emotion Recognition with Audio-visual Leader-follower Attentive Fusion
Su Zhang, Yi Ding, Ziquan Wei, Cuntai Guan
We propose an audio-visual spatial-temporal deep neural network with: (1) a visual block containing a pretrained 2D-CNN followed by a temporal convolutional network (TCN); (2) an aural block containing several parallel TCNs; and (3) a leader-follower attentive fusion block combining the audio-visual information. The TCN with large history coverage enables our model to exploit spatial-temporal information within a much larger window length (i.e., 300) than that from the baseline and state-of-the-art methods (i.e., 36 or 48). The fusion block emphasizes the visual modality while exploits the noisy aural modality using the inter-modality attention mechanism. To make full use of the data and alleviate over-fitting, cross-validation is carried out on the training and validation set. The concordance correlation coefficient (CCC) centering is used to merge the results from each fold. On the test (validation) set of the Aff-Wild2 database, the achieved CCC is 0.463 (0.469) for valence and 0.492 (0.649) for arousal, which significantly outperforms the baseline method with the corresponding CCC of 0.200 (0.210) and 0.190 (0.230) for valence and arousal, respectively. The code is available at https://github.com/sucv/ABAW2.
In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections