24 citations · 25 across the 4 of their papers we have counts for
6 papers
Multi-Domain Joint Training for Person Re-Identification
Lu Yang, Lingqiao Liu, Yunlong Wang +2
Deep learning-based person Re-IDentification (ReID) often requires a large amount of training data to achieve good performance. Thus it appears that collecting more training data f…
Learning Instance-level Spatial-Temporal Patterns for Person Re-identification
Min Ren, Lingxiao He, Xingyu Liao +3
Person re-identification (Re-ID) aims to match pedestrians under dis-joint cameras. Most Re-ID methods formulate it as visual representation learning and image search, and its accu…
Center Prediction Loss for Re-identification
Lu Yang, Yunlong Wang, Lingqiao Liu +5
The training loss function that enforces certain training sample distribution patterns plays a critical role in building a re-identification (ReID) system. Besides the basic requir…
Instance and Pair-Aware Dynamic Networks for Re-Identification
Bingliang Jiao, Xin Tan, Jinghao Zhou +3
Re-identification (ReID) is to identify the same instance across different cameras. Existing ReID methods mostly utilize alignment-based or attention-based strategies to generate e…
Directed Diversity: Leveraging Language Embedding Distances for Collective Creativity in Crowd Ideation
Samuel Rhys Cox, Yunlong Wang, Ashraf Abdul +2
Crowdsourcing can collect many diverse ideas by prompting ideators individually, but this can generate redundant ideas. Prior methods reduce redundancy by presenting peers' ideas o…
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection
Yue Zhao, Xiyang Hu, Cheng Cheng +11
Outlier detection (OD) is a key machine learning (ML) task for identifying abnormal objects from general samples with numerous high-stake applications including fraud detection and…