5 papers
Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis
Devinder Kumar, Parthipan Siva, Paul Marchwica +1
An ongoing major challenge in computer vision is the task of person re-identification, where the goal is to match individuals across different, non-overlapping camera views. While…
Fairest of Them All: Establishing a Strong Baseline for Cross-Domain Person ReID
Devinder Kumar, Parthipan Siva, Paul Marchwica +1
Person re-identification (ReID) remains a very difficult challenge in computer vision, and critical for large-scale video surveillance scenarios where an individual could appear in…
Exploiting Prunability for Person Re-Identification
Hugo Masson, Amran Bhuiyan, Le Thanh Nguyen-Meidine +4
Recent years have witnessed a substantial increase in the deep learning (DL)architectures proposed for visual recognition tasks like person re-identification,where individuals must…
An Evaluation of Deep CNN Baselines for Scene-Independent Person Re-Identification
Paul Marchwica, Michael Jamieson, Parthipan Siva
In recent years, a variety of proposed methods based on deep convolutional neural networks (CNNs) have improved the state of the art for large-scale person re-identification (ReID)…
Transfer Learning by Ranking for Weakly Supervised Object Annotation
Zhiyuan Shi, Parthipan Siva, Tao Xiang
Most existing approaches to training object detectors rely on fully supervised learning, which requires the tedious manual annotation of object location in a training set. Recently…