Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

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 (HPE) has developed over the past decade into a vibrant field for
research with a variety of real-world applications like 3D reconstruction, virtual testing and re …

The vision-language model has brought great improvement to few-shot industrial anomaly
detection which usually needs to design of hundreds of prompts through prompt …

Temporal modeling is crucial for multi-frame human pose estimation. Most existing methods
directly employ optical flow or deformable convolution to predict full-spectrum motion fields …

Human perception and understanding is a major domain of computer vision which like many
other vision subdomains recently stands to gain from the use of large models pre-trained on …

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 …

Despite the recent developments in the field of cross-modal retrieval, there has been less
research focusing on low-resource languages due to the lack of manually annotated …

We study the topic of large-scale few-shot image recognition with semantic-visual relational
knowledge-based transfer learning. Compared with classical few-shot learning, which is …

Training state-of-the-art models for human pose estimation in videos requires datasets with
annotations that are really hard and expensive to obtain. Although transformers have been …