77 citations · 130 across the 11 of their papers we have counts for
19 papers
Deep Insights of Learning based Micro Expression Recognition: A Perspective on Promises, Challenges and Research Needs
Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh
Micro expression recognition (MER) is a very challenging area of research due to its intrinsic nature and fine-grained changes. In the literature, the problem of MER has been solve…
RARITYNet: Rarity Guided Affective Emotion Learning Framework
Monu Verma, Santosh Kumar Vipparthi
Inspired from the assets of handcrafted and deep learning approaches, we proposed a RARITYNet: RARITY guided affective emotion learning framework to learn the appearance features a…
Cross-Centroid Ripple Pattern for Facial Expression Recognition
Monu Verma, Prafulla Saxena, Santosh Kumar Vipparthi +1
In this paper, we propose a new feature descriptor Cross-Centroid Ripple Pattern (CRIP) for facial expression recognition. CRIP encodes the transitional pattern of a facial express…
One for All: An End-to-End Compact Solution for Hand Gesture Recognition
Monu Verma, Ayushi Gupta, santosh kumar Vipparthi
The HGR is a quite challenging task as its performance is influenced by various aspects such as illumination variations, cluttered backgrounds, spontaneous capture, etc. The conven…
An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs
Murari Mandal, Santosh Kumar Vipparthi
Visual change detection, aiming at segmentation of video frames into foreground and background regions, is one of the elementary tasks in computer vision and video analytics. The a…
AffectiveNet: Affective-Motion Feature Learningfor Micro Expression Recognition
Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh
Micro-expressions are hard to spot due to fleeting and involuntary moments of facial muscles. Interpretation of micro emotions from video clips is a challenging task. In this paper…