113 citations · 353 across the 11 of their papers we have counts for
14 papers
GyroCopter: Differential Bearing Measuring Trajectory Planner for Tracking and Localizing Radio Frequency Sources
Fei Chen, S. Hamid Rezatofighi, Damith C. Ranasinghe
Autonomous aerial vehicles can provide efficient and effective solutions for radio frequency (RF) source tracking and localizing problems with applications ranging from wildlife co…
ConservationBots: Autonomous Aerial Robot for Fast Robust Wildlife Tracking in Complex Terrains
Fei Chen, Hoa Van Nguyen, David A. Taggart +3
Today, the most widespread, widely applicable technology for gathering data relies on experienced scientists armed with handheld radio telemetry equipment to locate low-power radio…
Towards Deep Clustering of Human Activities from Wearables
Alireza Abedin, Farbod Motlagh, Qinfeng Shi +2
Our ability to exploit low-cost wearable sensing modalities for critical human behaviour and activity monitoring applications in health and wellness is reliant on supervised learni…
Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks
Vineet Kosaraju, Amir Sadeghian, Roberto Martín-Martín +3
Predicting the future trajectories of multiple interacting agents in a scene has become an increasingly important problem for many different applications ranging from control of au…
CVPR19 Tracking and Detection Challenge: How crowded can it get?
Patrick Dendorfer, Hamid Rezatofighi, Anton Milan +6
Standardized benchmarks are crucial for the majority of computer vision applications. Although leaderboards and ranking tables should not be over-claimed, benchmarks often provide…
SparseSense: Human Activity Recognition from Highly Sparse Sensor Data-streams Using Set-based Neural Networks
Alireza Abedin, S. Hamid Rezatofighi, Qinfeng Shi +1
Batteryless or so called passive wearables are providing new and innovative methods for human activity recognition (HAR), especially in healthcare applications for older people. Pa…
Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak +3
Intersection over Union (IoU) is the most popular evaluation metric used in the object detection benchmarks. However, there is a gap between optimizing the commonly used distance l…
Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes
Yu Liu, Lingqiao Liu, Hamid Rezatofighi +3
As the post-processing step for object detection, non-maximum suppression (GreedyNMS) is widely used in most of the detectors for many years. It is efficient and accurate for spars…
Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables
Alireza Abedin Varamin, Ehsan Abbasnejad, Qinfeng Shi +2
Automatic recognition of human activities from time-series sensor data (referred to as HAR) is a growing area of research in ubiquitous computing. Most recent research in the field…
Deep Perm-Set Net: Learn to predict sets with unknown permutation and cardinality using deep neural networks
S. Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh +4
Many real-world problems, e.g. object detection, have outputs that are naturally expressed as sets of entities. This creates a challenge for traditional deep neural networks which…
Joint Learning of Set Cardinality and State Distribution
S. Hamid Rezatofighi, Anton Milan, Qinfeng Shi +2
We present a novel approach for learning to predict sets using deep learning. In recent years, deep neural networks have shown remarkable results in computer vision, natural langua…
DeepSetNet: Predicting Sets with Deep Neural Networks
S. Hamid Rezatofighi, Vijay Kumar B G, Anton Milan +3
This paper addresses the task of set prediction using deep learning. This is important because the output of many computer vision tasks, including image tagging and object detectio…
Online Multi-Target Tracking Using Recurrent Neural Networks
Anton Milan, Seyed Hamid Rezatofighi, Anthony Dick +2
We present a novel approach to online multi-target tracking based on recurrent neural networks (RNNs). Tracking multiple objects in real-world scenes involves many challenges, incl…
Multi-Target Tracking with Time-Varying Clutter Rate and Detection Profile: Application to Time-lapse Cell Microscopy Sequences
Seyed Hamid Rezatofighi, Stephen Gould, Ba Tuong Vo +3
Quantitative analysis of the dynamics of tiny cellular and sub-cellular structures, known as particles, in time-lapse cell microscopy sequences requires the development of a reliab…