89 citations · 108 across the 10 of their papers we have counts for
10 papers · 1 filter
Diffusion Models with Deterministic Normalizing Flow Priors
Mohsen Zand, Ali Etemad, Michael Greenspan
For faster sampling and higher sample quality, we propose DiNof (ffusion with rmalizing low priors), a technique that makes use of normalizing…
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…
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…
Keypoint Cascade Voting for Point Cloud Based 6DoF Pose Estimation
Yangzheng Wu, Alireza Javaheri, Mohsen Zand +1
We propose a novel keypoint voting 6DoF object pose estimation method, which takes pure unordered point cloud geometry as input without RGB information. The proposed cascaded keypo…
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…
Multiscale Crowd Counting and Localization By Multitask Point Supervision
Mohsen Zand, Haleh Damirchi, Andrew Farley +3
We propose a multitask approach for crowd counting and person localization in a unified framework. As the detection and localization tasks are well-correlated and can be jointly ta…
Multistream ValidNet: Improving 6D Object Pose Estimation by Automatic Multistream Validation
Joy Mazumder, Mohsen Zand, Michael Greenspan
This work presents a novel approach to improve the results of pose estimation by detecting and distinguishing between the occurrence of True and False Positive results. It achieves…
Oriented Bounding Boxes for Small and Freely Rotated Objects
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 pixels. Such tiny objects appear…
Flow-based Spatio-Temporal Structured Prediction of Motion Dynamics
Mohsen Zand, Ali Etemad, Michael Greenspan
Conditional Normalizing Flows (CNFs) are flexible generative models capable of representing complicated distributions with high dimensionality and large interdimensional correlatio…
Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting
Yangzheng Wu, Mohsen Zand, Ali Etemad +1
We propose a novel keypoint voting scheme based on intersecting spheres, that is more accurate than existing schemes and allows for fewer, more disperse keypoints. The scheme is ba…