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Multiple object tracking (MOT) has emerged as a crucial component of the rapidly developing computer vision. However, existing multi-object tracking methods often overlook the relationship between features and motion, hindering the ability to strike a ...

Speech super-resolution techniques offer a promising solution to enhance audio quality in wearable devices, particularly when addressing the challenges of reduced sampling rates necessitated by battery life constraints and network instability. However, ...

Recent studies have shown that image structure can significantly facilitate image inpainting. However, current approaches mostly explore structure prior without considering its guidance to texture reconstruction, leading to performance degradation. To ...

Category-level pose estimation is proposed to predict the 6D pose of objects under a specific category and has wide applications in fields such as robotics, virtual reality, and autonomous driving. With the development of VR/AR technology, pose estimation ...

This article presents the latest developments to ClaimBuster’s claim-spotting model, which tackles the critical task of identifying check-worthy claims from large streams of information. We introduce the first adversarially regularized, transformer-based ...

Understanding the part composition and structure of 3D shapes is crucial for a wide range of 3D applications, including 3D part assembly and 3D assembly completion. Compared to 3D part assembly, 3D assembly completion is more complicated, which involves ...

Trigger-action platforms (TAPs) enable users without programming experience to personalize the behavior of Internet of Things applications and services through IF-THEN rules. Unfortunately, the arbitrary connection of smart devices and online services, ...

In boiler power generation scenario, multi-modal data could be collected from the system, where main steam temperature could be the most important factor as it influence the whole power generation system's efficiency and safety. In this paper a time ...

Trajectory similarity computation is crucial for analyzing movement patterns in applications like traffic management and wildlife tracking. Recent self-supervised learning methods such as contrastive learning have made advancements in trajectory ...

Transformer-based methods have achieved impressive performance on temporal action localization (TAL). Although this achievement is attributed to the multiheaded self-attention (MSA) mechanism, there is still a lack of systematic understanding. ...

Detecting eye contact is essential for embodied robots to engage in natural interactions with humans, enhancing the intuitiveness and comfort of these exchanges. However, eye contact detection often presents a significant challenge due to a variety of ...

Engagement estimation is crucial for advancing natural human-computer interaction, allowing artificial agents to dynamically adjust their responses based on user engagement levels and creating more intuitive and immersive experiences. Despite ...

Expressive Human Mesh Recovery (HMR) involves reconstructing the 3D human body, including hands and face, from RGB images. It is difficult because humans are highly deformable, and hands are small and frequently occluded. Recent approaches have attempted ...

Audio-visual semantic segmentation (AVSS) aims to segment and classify sounding objects in videos with acoustic cues. However, most approaches operate on the close-set assumption and only identify pre-defined categories from training data, lacking the ...

The prevalence of multimedia applications has led to increased concerns and demand for auto face retouching. Face retouching aims to enhance portrait quality by removing blemishes. However, the existing auto-retouching methods rely heavily on a large ...

The wide use of mobile devices has led to a proliferated creation of extensive trajectory data, rendering trajectory classification increasingly vital and challenging for downstream applications. Existing deep learning methods offer powerful feature ...

Referring Remote Sensing Image Segmentation (RRSIS) is a challenging task that aims to identify specific regions in aerial images that are relevant to given textual conditions. Existing methods tend to adopt the paradigm of implicit optimization, ...

Video hashing is a technique of encoding videos into binary vectors, facilitating efficient video storage and high-speed computation. Current approaches to video hashing predominantly utilize sequential frame images to produce semantic binary codes. ...

Advances in computer vision research enable human-like high-dimensional perceptual induction over analogical visual reasoning problems, such as Raven's Progressive Matrices (RPMs). In this paper, we propose a Hierarchical Perception and Predictive ...

The burgeoning field of text-to-music generation models has shown great promise in their ability to generate high-quality music aligned with users' textual descriptions. These models effectively capture abstract/global musical features such as style and ...