Keypoint transformer: Solving joint identification in challenging hands and object interactions for accurate 3d pose estimation
We propose a robust and accurate method for estimating the 3D poses of two hands in close
interaction from a single color image. This is a very challenging problem, as large occlusions …
interaction from a single color image. This is a very challenging problem, as large occlusions …
Model-based 3d hand reconstruction via self-supervised learning
Reconstructing a 3D hand from a single-view RGB image is challenging due to various hand
configurations and depth ambiguity. To reliably reconstruct a 3D hand from a monocular …
configurations and depth ambiguity. To reliably reconstruct a 3D hand from a monocular …
Weakly supervised 3d hand pose estimation via biomechanical constraints
Estimating 3D hand pose from 2D images is a difficult, inverse problem due to the inherent
scale and depth ambiguities. Current state-of-the-art methods train fully supervised deep …
scale and depth ambiguities. Current state-of-the-art methods train fully supervised deep …
A2j-transformer: Anchor-to-joint transformer network for 3d interacting hand pose estimation from a single rgb image
Abstract 3D interacting hand pose estimation from a single RGB image is a challenging task,
due to serious self-occlusion and inter-occlusion towards hands, confusing similar …
due to serious self-occlusion and inter-occlusion towards hands, confusing similar …
End-to-end detection and pose estimation of two interacting hands
Three dimensional hand pose estimation has reached a level of maturity, enabling real-
world applications for single-hand cases. However, accurate estimation of the pose of two …
world applications for single-hand cases. However, accurate estimation of the pose of two …
Showme: Benchmarking object-agnostic hand-object 3d reconstruction
Recent hand-object interaction datasets show limited real object variability and rely on fitting
the MANO parametric model to obtain groundtruth hand shapes. To go beyond these …
the MANO parametric model to obtain groundtruth hand shapes. To go beyond these …
Visual-inertial hand motion tracking with robustness against occlusion, interference, and contact
State-of-the-art technologies for hand (and finger) motion tracking do not always provide
accurate and robust tracking. For example, severe occlusions can affect tracking with vision …
accurate and robust tracking. For example, severe occlusions can affect tracking with vision …
Two heads are better than one: Image-point cloud network for depth-based 3d hand pose estimation
Depth images and point clouds are the two most commonly used data representations for
depth-based 3D hand pose estimation. Benefiting from the structuring of image data and the …
depth-based 3D hand pose estimation. Benefiting from the structuring of image data and the …
I2uv-handnet: Image-to-uv prediction network for accurate and high-fidelity 3d hand mesh modeling
Reconstructing a high-precision and high-fidelity 3D human hand from a color image plays a
central role in replicating a realistic virtual hand in human-computer interaction and virtual …
central role in replicating a realistic virtual hand in human-computer interaction and virtual …