2.9k citations · 10.7k across the 136 of their papers we have counts for
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Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation
Haowen Deng, Mai Bui, Nassir Navab +3
In this work, we introduce Deep Bingham Networks (DBN), a generic framework that can naturally handle pose-related uncertainties and ambiguities arising in almost all real life app…
Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments
Siyan Dong, Qingnan Fan, He Wang +5
Localizing the camera in a known indoor environment is a key building block for scene mapping, robot navigation, AR, etc. Recent advances estimate the camera pose via optimization…
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection
He Wang, Yezhen Cong, Or Litany +2
3D object detection is an important yet demanding task that heavily relies on difficult to obtain 3D annotations. To reduce the required amount of supervision, we propose 3DIoUMatc…
Towards Accurate Active Camera Localization
Qihang Fang, Yingda Yin, Qingnan Fan +6
In this work, we tackle the problem of active camera localization, which controls the camera movements actively to achieve an accurate camera pose. The past solutions are mostly ba…
Generative Layout Modeling using Constraint Graphs
Wamiq Para, Paul Guerrero, Tom Kelly +2
We propose a new generative model for layout generation. We generate layouts in three steps. First, we generate the layout elements as nodes in a layout graph. Second, we compute c…
A Point-Cloud Deep Learning Framework for Prediction of Fluid Flow Fields on Irregular Geometries
Ali Kashefi, Davis Rempe, Leonidas J. Guibas
We present a novel deep learning framework for flow field predictions in irregular domains when the solution is a function of the geometry of either the domain or objects inside th…