Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We
have created various computer-mediated virtual environments, including social networks …

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 …

We propose DiffusionDet, a new framework that formulates object detection as a denoising
diffusion process from noisy boxes to object boxes. During the training stage, object boxes …

Accurate whole-body multi-person pose estimation and tracking is an important yet
challenging topic in computer vision. To capture the subtle actions of humans for complex …

We present an approach to reconstruct humans and track them over time. At the core of our
approach, we propose a fully" transformerized" version of a network for human mesh …

In this paper, a novel Diffusion-based 3D Pose estimation (D3DP) method with Joint-wise
reProjection-based Multi-hypothesis Aggregation (JPMA) is proposed for probabilistic 3D …

Transformer architectures have become the model of choice in natural language processing
and are now being introduced into computer vision tasks such as image classification, object …

We present an efficient high-resolution network, Lite-HRNet, for human pose estimation. We
start by simply applying the efficient shuffle block in ShuffleNet to HRNet (high-resolution …

Human pose is typically represented by a coordinate vector of body joints or their heatmap
embeddings. While easy for data processing, unrealistic pose estimates are admitted due to …

In this paper, we are interested in the bottom-up paradigm of estimating human poses from
an image. We study the dense keypoint regression framework that is previously inferior to …