2 citations · 2 across the 4 of their papers we have counts for
4 papers
Multiscale Residual Learning of Graph Convolutional Sequence Chunks for Human Motion Prediction
Mohsen Zand, Ali Etemad, Michael Greenspan
A new method is proposed for human motion prediction by learning temporal and spatial dependencies. Recently, multiscale graphs have been developed to model the human body at highe…
Learning Better Keypoints for Multi-Object 6DoF Pose Estimation
Yangzheng Wu, Michael Greenspan
We address the problem of keypoint selection, and find that the performance of 6DoF pose estimation methods can be improved when pre-defined keypoint locations are learned, rather…
Diffusion Dataset Generation: Towards Closing the Sim2Real Gap for Pedestrian Detection
Andrew Farley, Mohsen Zand, Michael Greenspan
We propose a method that augments a simulated dataset using diffusion models to improve the performance of pedestrian detection in real-world data. The high cost of collecting and…
ObjectBox: From Centers to Boxes for Anchor-Free Object Detection
Mohsen Zand, Ali Etemad, Michael Greenspan
We present ObjectBox, a novel single-stage anchor-free and highly generalizable object detection approach. As opposed to both existing anchor-based and anchor-free detectors, which…