Re-Id12
* *International Workshop on Re-identification
* General Method for Appearance-Based People Search Based on Textual Queries, A
* Identity Inference: Generalizing Person Re-identification Scenarios
* Learning Implicit Transfer for Person Re-identification
* Local Descriptors Encoded by Fisher Vectors for Person Re-identification
* Person Re-identification: What Features Are Important?
* Re-identification of Pedestrians in Crowds Using Dynamic Time Warping
* Re-identification with RGB-D Sensors
* Towards Person Identification and Re-identification with Attributes
9 for Re-Id12
Re-Id14
* *International Workshop on Re-identification
* Calibration Methodology for Distant Surveillance Cameras
* HDA+ Data Set for Research on Fully Automated Re-identification Systems, The
* Improving Global Multi-target Tracking with Local Updates
* Investigating Open-World Person Re-identification Using a Drone
* Joint Learning for Attribute-Consistent Person Re-Identification
* Learning Action Primitives for Multi-level Video Event Understanding
* Learning Skeleton Stream Patterns with Slow Feature Analysis for Action Recognition
* Novel Visual Word Co-occurrence Model for Person Re-identification, A
* Person Re-identification by Discriminatively Selecting Parts and Features
* Regularized Bayesian Metric Learning for Person Re-identification
* Saliency Weighted Features for Person Re-identification
12 for Re-Id14
Re-Id17
* *Target Re-identification and Multi-target Multi-camera Tracking
* Dataset for Persistent Multi-target Multi-camera Tracking in RGB-D, A
* Deep Spatial-Temporal Fusion Network for Video-Based Person Re-identification
* DukeMTMC4ReID: A Large-Scale Multi-camera Person Re-identification Dataset
* Person Re-identification by Deep Learning Attribute-Complementary Information
* Towards a Principled Integration of Multi-camera Re-identification and Tracking Through Optimal Bayes Filters
* Track-Clustering Error Evaluation for Track-Based Multi-camera Tracking System Employing Human Re-identification
* Trajectory Ensemble: Multiple Persons Consensus Tracking Across Non-overlapping Multiple Cameras over Randomly Dropped Camera Networks
* Video-Based Person Re-identification by Deep Feature Guided Pooling
9 for Re-Id17