Martin Engelcke
Cited by
Cited by
Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks
M Engelcke, D Rao, DZ Wang, CH Tong, I Posner
Proceedings of the IEEE International Conference on Robotics and Automation …, 2017
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
B Graham, M Engelcke, L van der Maaten
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
L Yi, L Shao, M Savva, H Huang, Y Zhou, Q Wang, B Graham, M Engelcke, ...
arXiv preprint arXiv:1710.06104, 2017
On the Limitations of Representing Functions on Sets
E Wagstaff, FB Fuchs, M Engelcke, I Posner, M Osborne
International Conference on Machine Learning (ICML), 2019
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
M Engelcke, AR Kosiorek, O Parker Jones, I Posner
International Conference on Learning Representations (ICLR), 2020
Analyzing Spatially-Sparse Data Based on Submanifold Sparse Convolutional Neural Networks
BT Graham, LJP van der Maaten, MH Engelcke
US Patent App. 16/193,735, 2019
Reconstruction Bottlenecks in Object-Centric Generative Models
M Engelcke, OP Jones, I Posner
Workshop on Object-Oriented Learning at ICML 2020, 2020
First Steps: Latent-Space Control with Semantic Constraints for Quadruped Locomotion
AL Mitchell, M Engelcke, OP Jones, D Surovik, I Havoutis, I Posner
arXiv preprint arXiv:2007.01520, 2020
RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces
S Ehrhardt, O Groth, A Monszpart, M Engelcke, I Posner, N Mitra, ...
arXiv preprint arXiv:2007.01272, 2020
A Neural Network and Method of Using a Neural Network to Detect Objects in an Environment
M Engelcke, D Rao, DZ Wang, CH Tong, I Posner
EP Patent App. 20,170,777,642, 2019
The system can't perform the operation now. Try again later.
Articles 1–10