25 citations · 30 across the 4 of their papers we have counts for
7 papers · 1 filter
Self-Supervised Robust Scene Flow Estimation via the Alignment of Probability Density Functions
Pan He, Patrick Emami, Sanjay Ranka +1
In this paper, we present a new self-supervised scene flow estimation approach for a pair of consecutive point clouds. The key idea of our approach is to represent discrete point c…
Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations
Patrick Emami, Pan He, Sanjay Ranka +1
Unsupervised multi-object representation learning depends on inductive biases to guide the discovery of object-centric representations that generalize. However, we observe that met…
SparsePipe: Parallel Deep Learning for 3D Point Clouds
Keke Zhai, Pan He, Tania Banerjee +2
We propose SparsePipe, an efficient and asynchronous parallelism approach for handling 3D point clouds with multi-GPU training. SparsePipe is built to support 3D sparse data such a…
Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near Accident Detection in Traffic Video
Xiaohui Huang, Pan He, Anand Rangarajan +1
In Intelligent Transportation System, real-time systems that monitor and analyze road users become increasingly critical as we march toward the smart city era. Vision-based framewo…
Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification
Chengliang Yang, Anand Rangarajan, Sanjay Ranka
We develop three efficient approaches for generating visual explanations from 3D convolutional neural networks (3D-CNNs) for Alzheimer's disease classification. One approach conduc…
Machine Learning Methods for Data Association in Multi-Object Tracking
Patrick Emami, Panos M. Pardalos, Lily Elefteriadou +1
Data association is a key step within the multi-object tracking pipeline that is notoriously challenging due to its combinatorial nature. A popular and general way to formulate dat…