Search Results for author: Michael Greenspan

Found 11 papers, 4 papers with code

Multistream ValidNet: Improving 6D Object Pose Estimation by Automatic Multistream Validation

no code implementations12 Jun 2021 Joy Mazumder, Mohsen Zand, Michael Greenspan

Applying our method can also improve the pose estimation average precision results of Op-Net by 6. 06% on average.

6D Pose Estimation using RGB

Oriented Bounding Boxes for Small and Freely Rotated Objects

no code implementations24 Apr 2021 Mohsen Zand, Ali Etemad, Michael Greenspan

A novel object detection method is presented that handles freely rotated objects of arbitrary sizes, including tiny objects as small as $2\times 2$ pixels.

Object Detection

Flow-based Autoregressive Structured Prediction of Human Motion

no code implementations9 Apr 2021 Mohsen Zand, Ali Etemad, Michael Greenspan

A new method is proposed for human motion predition by learning temporal and spatial dependencies in an end-to-end deep neural network.

motion prediction Structured Prediction

Teacher-Student Adversarial Depth Hallucination to Improve Face Recognition

1 code implementation ICCV 2021 Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan, Ali Etemad

Moreover, face recognition experiments demonstrate that our hallucinated depth along with the input RGB images boosts performance across various architectures when compared to a single RGB modality by average values of +1. 2%, +2. 6%, and +2. 6% for IIIT-D, EURECOM, and LFW datasets respectively.

Face Recognition

Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting

no code implementations6 Apr 2021 Yangzheng Wu, Mohsen Zand, Ali Etemad, Michael Greenspan

We propose a novel keypoint voting scheme based on intersecting spheres, that is more accurate than existing schemes and allows for a smaller set of more disperse keypoints.

Pose Estimation

Procam Calibration from a Single Pose of a Planar Target

no code implementations22 Feb 2021 Ghani O. Lawal, Michael Greenspan

A novel user friendly method is proposed for calibrating a procam system from a single pose of a planar chessboard target.

Depth as Attention for Face Representation Learning

1 code implementation3 Jan 2021 Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan, Ali Etemad

Our novel attention mechanism directs the deep network "where to look" for visual features in the RGB image by focusing the attention of the network using depth features extracted by a Convolution Neural Network (CNN).

Face Recognition Representation Learning

Exploring End-to-End Differentiable Natural Logic Modeling

1 code implementation COLING 2020 Yufei Feng, Zi'ou Zheng, Quan Liu, Michael Greenspan, Xiaodan Zhu

We explore end-to-end trained differentiable models that integrate natural logic with neural networks, aiming to keep the backbone of natural language reasoning based on the natural logic formalism while introducing subsymbolic vector representations and neural components.

Deriving Commonsense Inference Tasks from Interactive Fictions

no code implementations19 Oct 2020 Mo Yu, Xiaoxiao Guo, Yufei Feng, Xiaodan Zhu, Michael Greenspan, Murray Campbell

Commonsense reasoning simulates the human ability to make presumptions about our physical world, and it is an indispensable cornerstone in building general AI systems.

Reading Comprehension

Two-Level Attention-based Fusion Learning for RGB-D Face Recognition

1 code implementation29 Feb 2020 Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan, Ali Etemad

A novel attention aware method is proposed to fuse two image modalities, RGB and depth, for enhanced RGB-D facial recognition.

Face Recognition Transfer Learning

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