activity
20212026
most citedContinuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition

3 citations · 8 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Shape-Bayes: Bayesian Inference of Structured Shapes under Visual Ambiguity

Mani Kumar Tellamekala, Tosh Brown, Michel Valstar

Perceiving structured shapes, such as human faces, from pixels is an inherently ambiguous task in real-world conditions. Yet, shape inference is largely posed as a deterministic re…

cs.CV2025

xTrace: A Facial Expressive Behaviour Analysis Tool for Continuous Affect Recognition

Mani Kumar Tellamekala, Shashank Jaiswal, Thomas Smith +4

Recognising expressive behaviours in face videos is a long-standing challenge in Affective Computing. Despite significant advancements in recent years, it still remains a challenge…

cs.CV2022★ 2 cited

Are 3D Face Shapes Expressive Enough for Recognising Continuous Emotions and Action Unit Intensities?

Mani Kumar Tellamekala, Ömer Sümer, Björn W. Schuller +3

Recognising continuous emotions and action unit (AU) intensities from face videos requires a spatial and temporal understanding of expression dynamics. Existing works primarily rel…

cs.CV2022★ 3 cited

COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognition

Mani Kumar Tellamekala, Shahin Amiriparian, Björn W. Schuller +3

Automatically recognising apparent emotions from face and voice is hard, in part because of various sources of uncertainty, including in the input data and the labels used in a mac…

cs.SD2022★ 3 cited

Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition

Vincent Karas, Mani Kumar Tellamekala, Adria Mallol-Ragolta +2

In this paper, we present our submission to 3rd Affective Behavior Analysis in-the-wild (ABAW) challenge. Learningcomplex interactions among multimodal sequences is critical to rec…

cs.CV2021

Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition

Enrique Sanchez, Mani Kumar Tellamekala, Michel Valstar +1

Temporal context is key to the recognition of expressions of emotion. Existing methods, that rely on recurrent or self-attention models to enforce temporal consistency, work on the…