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Found 9 papers, 5 papers with code
Rethinking Affect Analysis: A Protocol for Ensuring Fairness and Consistency
Evaluating affect analysis methods presents challenges due to inconsistencies in database partitioning and evaluation protocols, leading to unfair and biased results.
Robust Facial Reactions Generation: An Emotion-Aware Framework with Modality Compensation
In scenarios where speech modality data is missing, the performance of appropriate generation shows an improvement, and when facial data is missing, it only exhibits minimal degradation.
Efficient Temporal Action Segmentation via Boundary-aware Query Voting
Although the performance of Temporal Action Segmentation (TAS) has improved in recent years, achieving promising results often comes with a high computational cost due to dense inputs, complex model structures, and resource-intensive post-processing requirements.
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Bridging the Gap: Protocol Towards Fair and Consistent Affect Analysis
Automatic affect analysis, at the intersection of physiology, psychology, and machine learning, has seen significant development.
Image Prior and Posterior Conditional Probability Representation for Efficient Damage Assessment
It is important to quantify Damage Assessment (DA) for Human Assistance and Disaster Response (HADR) applications.
Transparent Object Tracking with Enhanced Fusion Module
However, with the existing fusion techniques, the addition of new features causes a change in the latent space making it impossible to incorporate transparency awareness on trackers with fixed latent spaces.
Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?
This paper studies the principal component (PC) method-based estimation of weak factor models with sparse loadings.
CCTV-Gun: Benchmarking Handgun Detection in CCTV Images
In this paper, we present a meticulously crafted and annotated benchmark, called \textbf{CCTV-Gun}, which addresses the challenges of detecting handguns in real-world CCTV images.
NIDA-CLIFGAN: Natural Infrastructure Damage Assessment through Efficient Classification Combining Contrastive Learning, Information Fusion and Generative Adversarial Networks
During natural disasters, aircraft and satellites are used to survey the impacted regions.
