Recovering a skeletal shape from a monocular video is a longstanding challenge. Prevailing
nonrigid animal reconstruction methods often adopt a control-point driven animation model …

Reconstructing the 3D articulated shape of an animal from a single in-the-wild image is a
challenging task. We propose LEPARD, a learning-based framework that discovers …

We present a method for reconstructing articulated 3D models from videos in real-time,
without test-time optimization or manual 3D supervision at training time. Prior work often …

In this paper we address the challenge of reconstructing general articulated 3D objects from
a single video. Existing works employing dynamic neural radiance fields have advanced the …

We introduce SAOR a novel approach for estimating the 3D shape texture and viewpoint of
an articulated object from a single image captured in the wild. Unlike prior approaches that …

Estimating 3D articulated shapes like animal bodies from monocular images is inherently
challenging due to the ambiguities of camera viewpoint, pose, texture, lighting, etc. We …

We introduce ViSER, a method for recovering articulated 3D shapes and dense3D
trajectories from monocular videos. Previous work on high-quality reconstruction of dynamic …

Remarkable progress has been made in 3D reconstruction of rigid structures from a video or
a collection of images. However, it is still challenging to reconstruct nonrigid structures from …

Creating high-quality articulated 3D models of animals is challenging either via manual
creation or using 3D scanning tools. Therefore, techniques to reconstruct articulated 3D …

Prior work for articulated 3D shape reconstruction often relies on specialized multi-view and
depth sensors or pre-built deformable 3D models. Such methods do not scale to diverse sets …