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Found 7 papers, 1 papers with code
On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data.
Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression
Depth estimation is a core task in 3D computer vision.
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.
Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction
Current 6D object pose methods consist of deep CNN models fully optimized for a single object but with its architecture standardized among objects with different shapes.
Learning to Align Semantic Segmentation and 2.5D Maps for Geolocalization
We present an efficient method for geolocalization in urban environments starting from a coarse estimate of the location provided by a GPS and using a simple untextured 2. 5D model of the surrounding buildings.
What is usual in unusual videos? Trajectory snippet histograms for discovering unusualness
Unusual events are important as being possible indicators of undesired consequences.
