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Found 17 papers, 5 papers with code
HandDGP: Camera-Space Hand Mesh Prediction with Differentiable Global Positioning
Predicting camera-space hand meshes from single RGB images is crucial for enabling realistic hand interactions in 3D virtual and augmented worlds.
DoubleTake: Geometry Guided Depth Estimation
Estimating depth from a sequence of posed RGB images is a fundamental computer vision task, with applications in augmented reality, path planning etc.
Removing Objects From Neural Radiance Fields
We validate our approach using a new and still-challenging dataset for the task of NeRF inpainting.
Map-free Visual Relocalization: Metric Pose Relative to a Single Image
Can we relocalize in a scene represented by a single reference image?
Predicting Visual Overlap of Images Through Interpretable Non-Metric Box Embeddings
Even when this is a known scene, the answer typically requires an expensive search across scale space, with matching and geometric verification of large sets of local features.
Physics-Based Dexterous Manipulations with Estimated Hand Poses and Residual Reinforcement Learning
Dexterous manipulation of objects in virtual environments with our bare hands, by using only a depth sensor and a state-of-the-art 3D hand pose estimator (HPE), is challenging.
Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction
To address these issues, we designed a public challenge (HANDS'19) to evaluate the abilities of current 3D hand pose estimators (HPEs) to interpolate and extrapolate the poses of a training set.
Introducing Pose Consistency and Warp-Alignment for Self-Supervised 6D Object Pose Estimation in Color Images
Most successful approaches to estimate the 6D pose of an object typically train a neural network by supervising the learning with annotated poses in real world images.
A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators
In this paper, we present the first comprehensive and most recent review of the methods on object pose recovery, from 3D bounding box detectors to full 6D pose estimators.
Active 6D Multi-Object Pose Estimation in Cluttered Scenarios with Deep Reinforcement Learning
In this work, we explore how a strategic selection of camera movements can facilitate the task of 6D multi-object pose estimation in cluttered scenarios while respecting real-world constraints important in robotics and augmented reality applications, such as time and distance traveled.
Instance- and Category-level 6D Object Pose Estimation
6D object pose estimation is an important task that determines the 3D position and 3D rotation of an object in camera-centred coordinates.
HANDS18: Methods, Techniques and Applications for Hand Observation
The fourth instantiation of this workshop attracted significant interest from both academia and the industry.
Task-Oriented Hand Motion Retargeting for Dexterous Manipulation Imitation
In this work, we capture the hand information by using a state-of-the-art hand pose estimator.
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018
Ranked #5 on
Hand Pose Estimation
on HANDS 2017
The 2017 Hands in the Million Challenge on 3D Hand Pose Estimation
We present the 2017 Hands in the Million Challenge, a public competition designed for the evaluation of the task of 3D hand pose estimation.
First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations
Our dataset and experiments can be of interest to communities of 3D hand pose estimation, 6D object pose, and robotics as well as action recognition.
Transition Forests: Learning Discriminative Temporal Transitions for Action Recognition and Detection
A human action can be seen as transitions between one's body poses over time, where the transition depicts a temporal relation between two poses.
