2 citations · 2 across the 4 of their papers we have counts for
6 papers · 1 filter
Free-Moving Object Reconstruction and Pose Estimation with Virtual Camera
Haixin Shi, Yinlin Hu, Daniel Koguciuk +3
We propose an approach for reconstructing free-moving object from a monocular RGB video. Most existing methods either assume scene prior, hand pose prior, object category pose prio…
HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields
Haozhe Qi, Chen Zhao, Mathieu Salzmann +1
Human hands are highly articulated and versatile at handling objects. Jointly estimating the 3D poses of a hand and the object it manipulates from a monocular camera is challenging…
Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes
Andrey Davydov, Alexey Sidnev, Artsiom Sanakoyeu +3
When enough annotated training data is available, supervised deep-learning algorithms excel at estimating human body pose and shape using a single camera. The effects of too little…
GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondence
Van Nguyen Nguyen, Thibault Groueix, Mathieu Salzmann +1
We present GigaPose, a fast, robust, and accurate method for CAD-based novel object pose estimation in RGB images. GigaPose first leverages discriminative "templates", rendered ima…
3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation
Chen Zhao, Tong Zhang, Mathieu Salzmann
Prior methods that tackle the problem of generalizable object pose estimation highly rely on having dense views of the unseen object. By contrast, we address the scenario where onl…
Understanding Pose and Appearance Disentanglement in 3D Human Pose Estimation
Krishna Kanth Nakka, Mathieu Salzmann
As 3D human pose estimation can now be achieved with very high accuracy in the supervised learning scenario, tackling the case where 3D pose annotations are not available has recei…