September 2026

Existing head pose estimation (HPE) methods focus on utilizing the information of one single image and ignore cross-viewpoint pose consistency. To remedy this, we propose a dual-branch self-correcting

Existing methods typically require training a separate model for each dataset, making them difficult to generalize across diverse illumination conditions. To address this limitation, we propose a nove

Video segmentation and image segmentation share inherent similarities, yet existing video segmentation methods often rely on dedicated architectural redesign. This results in redundant computation and

Large-scale indoor mapping and positioning with vision sensors is fundamental to a wide range of applications, such as robotic navigation and augmented reality. However, the rapidly increasing number

Diffusion- and flow-based generative models have achieved strong performance in speech enhancement, but they typically rely on an explicit time variable to specify the generation stage. Since the nois

Interstitial lung disease (ILD) screening from respiratory sounds (RSs) remains challenging due to the subtle acoustic differences between pathological and healthy patterns, compounded by limited labe

Mixture of Experts (MoE) models are a promising approach for Speech Emotion Recognition (SER), but they often rely on a fixed top-$k$ routing rule, which limits their ability to adapt expert activatio

With the development of Artificial Intelligence (AI), deep neural networks have shown promising capabilities for image signal processing tasks. However, in practical applications of image processing a

Event-stream denoising can irreversibly remove valid events around sparse contours, weak textures, and fast-moving structures when filtering decisions are treated as terminal. This letter proposes rec

No-Reference Image Quality Assessment (NR-IQA) aims to predict perceptual image quality from distorted images without reference signals. Existing NR-IQA methods often incorporate visual attention thro