most citedAbs-CAM: A Gradient Optimization Interpretable Approach for Explanation of Convolutional Neural Networks

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

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cs.CV20241 cited

LLDif: Diffusion Models for Low-light Emotion Recognition

Zhifeng Wang, Kaihao Zhang, Ramesh Sankaranarayana

This paper introduces LLDif, a novel diffusion-based facial expression recognition (FER) framework tailored for extremely low-light (LL) environments. Images captured under such co…

cs.CV2024

Authentic Emotion Mapping: Benchmarking Facial Expressions in Real News

Qixuan Zhang, Zhifeng Wang, Yang Liu +4

In this paper, we present a novel benchmark for Emotion Recognition using facial landmarks extracted from realistic news videos. Traditional methods relying on RGB images are resou…

cs.CV2024

LRDif: Diffusion Models for Under-Display Camera Emotion Recognition

Zhifeng Wang, Kaihao Zhang, Ramesh Sankaranarayana

This study introduces LRDif, a novel diffusion-based framework designed specifically for facial expression recognition (FER) within the context of under-display cameras (UDC). To a…

cs.CV2023

Using Scene and Semantic Features for Multi-modal Emotion Recognition

Zhifeng Wang, Ramesh Sankaranarayana

Automatic emotion recognition is a hot topic with a wide range of applications. Much work has been done in the area of automatic emotion recognition in recent years. The focus has…

cs.CV2023

HTNet for micro-expression recognition

Zhifeng Wang, Kaihao Zhang, Wenhan Luo +1

Facial expression is related to facial muscle contractions and different muscle movements correspond to different emotional states. For micro-expression recognition, the muscle mov…

cs.CV20223 cited

Abs-CAM: A Gradient Optimization Interpretable Approach for Explanation of Convolutional Neural Networks

Chunyan Zeng, Kang Yan, Zhifeng Wang +3

The black-box nature of Deep Neural Networks (DNNs) severely hinders its performance improvement and application in specific scenes. In recent years, class activation mapping-based…