Search Results for author: Haowen Deng

Found 7 papers, 5 papers with code

Potential Convolution: Embedding Point Clouds into Potential Fields

no code implementations5 Apr 2021 Dengsheng Chen, Haowen Deng, Jun Li, Duo Li, Yao Duan, Kai Xu

In this work, rather than defining a continuous or discrete kernel, we directly embed convolutional kernels into the learnable potential fields, giving rise to potential convolution.

3D Shape Classification Scene Segmentation

Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation

1 code implementation20 Dec 2020 Haowen Deng, Mai Bui, Nassir Navab, Leonidas Guibas, Slobodan Ilic, Tolga Birdal

For the former we contributed our own dataset composed of five indoor scenes where it is unavoidable to capture images corresponding to views that are hard to uniquely identify.

Camera Relocalization Pose Estimation

6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference

2 code implementations ECCV 2020 Mai Bui, Tolga Birdal, Haowen Deng, Shadi Albarqouni, Leonidas Guibas, Slobodan Ilic, Nassir Navab

We present a multimodal camera relocalization framework that captures ambiguities and uncertainties with continuous mixture models defined on the manifold of camera poses.

Camera Relocalization

3D Local Features for Direct Pairwise Registration

no code implementations CVPR 2019 Haowen Deng, Tolga Birdal, Slobodan Ilic

Our extensive quantitative and qualitative experiments suggests that our approach outperforms the state of the art in challenging real datasets of pairwise registration and that augmenting the keypoints with local pose information leads to better generalization and a dramatic speed-up.

Pose Estimation

3D Point Capsule Networks

2 code implementations CVPR 2019 Yongheng Zhao, Tolga Birdal, Haowen Deng, Federico Tombari

In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data.

3D Feature Matching 3D Geometry Perception +7

PPFNet: Global Context Aware Local Features for Robust 3D Point Matching

1 code implementation CVPR 2018 Haowen Deng, Tolga Birdal, Slobodan Ilic

We present PPFNet - Point Pair Feature NETwork for deeply learning a globally informed 3D local feature descriptor to find correspondences in unorganized point clouds.

Point Cloud Registration

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