3 citations · 7 across the 5 of their papers we have counts for
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Class adaptive threshold and negative class guided noisy annotation robust Facial Expression Recognition
Darshan Gera, Badveeti Naveen Siva Kumar, Bobbili Veerendra Raj Kumar +1
The hindering problem in facial expression recognition (FER) is the presence of inaccurate annotations referred to as noisy annotations in the datasets. These noisy annotations are…
Masked Student Dataset of Expressions
Sridhar Sola, Darshan Gera
Facial expression recognition (FER) algorithms work well in constrained environments with little or no occlusion of the face. However, real-world face occlusion is prevalent, most…
ABAW : Facial Expression Recognition in the wild
Darshan Gera, Badveeti Naveen Siva Kumar, Bobbili Veerendra Raj Kumar +1
The fifth Affective Behavior Analysis in-the-wild (ABAW) competition has multiple challenges such as Valence-Arousal Estimation Challenge, Expression Classification Challenge, Acti…
Dynamic Adaptive Threshold based Learning for Noisy Annotations Robust Facial Expression Recognition
Darshan Gera, Naveen Siva Kumar Badveeti, Bobbili Veerendra Raj Kumar +1
The real-world facial expression recognition (FER) datasets suffer from noisy annotations due to crowd-sourcing, ambiguity in expressions, the subjectivity of annotators and inter-…
SS-MFAR : Semi-supervised Multi-task Facial Affect Recognition
Darshan Gera, Badveeti Naveen Siva Kumar, Bobbili Veerendra Raj Kumar +1
Automatic affect recognition has applications in many areas such as education, gaming, software development, automotives, medical care, etc. but it is non trivial task to achieve a…