The recent amalgamation of transformer and convolutional designs has led to steady
improvements in accuracy and efficiency of the models. In this work, we introduce FastViT, a …

We present an approach that can reconstruct hands in 3D from monocular input. Our
approach for Hand Mesh Recovery HaMeR follows a fully transformer-based architecture …

Humans commonly work with multiple objects in daily life and can intuitively transfer
manipulation skills to novel objects by understanding object functional regularities. However …

Estimating the articulated 3D hand-object pose from a single RGB image is a highly
ambiguous and challenging problem, requiring large-scale datasets that contain diverse …

Hand, the bearer of human productivity and intelligence, is receiving much attention due to
the recent fever of digital twins. Among different hand morphable models, MANO has been …

Despite the impressive performance obtained by recent single-image hand modeling
techniques, they lack the capability to capture sufficient details of the 3D hand mesh. This …

Real-time 3D hand mesh reconstruction is challenging, especially when the hand is holding
some object. Beyond the previous methods, we design H2ONet to fully exploit non-occluded …

Recent years have witnessed a trend of the deep integration of the generation and
reconstruction paradigms. In this paper we extend the ability of controllable generative …

Over the last few years, with the advent of virtual and augmented reality, an enormous
amount of research has been focused on modeling, tracking and reconstructing human …

Reconstructing interacting hands from a single RGB image is a very challenging task. On the
one hand, severe mutual occlusion and similar local appearance between two hands …