Human Pose Estimation (HPE) is the task that aims to predict the location of human joints
from images and videos. This task is used in many applications, such as sports analysis and …

Denoising diffusion probabilistic models that were initially proposed for realistic image
generation have recently shown success in various perception tasks (eg, object detection …

Human pose estimation in videos has long been a compelling yet challenging task within
the realm of computer vision. Nevertheless, this task remains difficult because of the …

Human pose analysis has garnered significant attention within both the research community
and practical applications, owing to its expanding array of uses, including gaming, video …

An effective pre-training framework with universal 3D representations is extremely desired in
perceiving large-scale dynamic scenes. However establishing such an ideal framework that …

Human pose forecasting garners attention for its diverse applications. However challenges
in modeling the multi-modal nature of human motion and intricate interactions among agents …

In this paper, SEPAM_HRNet, a high-resolution pose-estimation model that incorporates the
squeeze-and-excitation and pixel-attention-mask (SEPAM) module is proposed. Feature …

We propose a novel transformer-based framework that reconstructs two high fidelity hands
from multi-view RGB images. Unlike existing hand pose estimation methods, where one …

By leveraging temporal dependency in video sequences multi-frame human pose estimation
algorithms have demonstrated remarkable results in complicated situations such as …

Despite progress in video-language modeling, the computational challenge of interpreting
long-form videos in response to task-specific linguistic queries persists, largely due to the …