20 citations · 54 across the 11 of their papers we have counts for
13 papers
More Data, Worse Decisions? Preference Reversals in Neural Networks under Gram Incompatibility
Yanli Yan, Yuanzheng Li, Yong Zhao +2
Neural networks increasingly combine data across populations, time periods, and operating conditions to improve generalization. This raises a reliability question: whether a model…
SCING:Towards More Efficient and Robust Person Re-Identification through Selective Cross-modal Prompt Tuning
Yunfei Xie, Yuxuan Cheng, Juncheng Wu +3
Recent advancements in adapting vision-language pre-training models like CLIP for person re-identification (ReID) tasks often rely on complex adapter design or modality-specific tu…
Focus On Details: Online Multi-object Tracking with Diverse Fine-grained Representation
Hao Ren, Shoudong Han, Huilin Ding +3
Discriminative representation is essential to keep a unique identifier for each target in Multiple object tracking (MOT). Some recent MOT methods extract features of the bounding b…
Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation
En Yu, Songtao Liu, Zhuoling Li +4
Although existing multi-object tracking (MOT) algorithms have obtained competitive performance on various benchmarks, almost all of them train and validate models on the same domai…
Towards Discriminative Representation: Multi-view Trajectory Contrastive Learning for Online Multi-object Tracking
En Yu, Zhuoling Li, Shoudong Han
Discriminative representation is crucial for the association step in multi-object tracking. Recent work mainly utilizes features in single or neighboring frames for constructing me…
Towards Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-based Method
Tao Bai, Jun Zhao, Jinlin Zhu +4
Intelligent Internet of Things (IoT) systems based on deep neural networks (DNNs) have been widely deployed in the real world. However, DNNs are found to be vulnerable to adversari…
RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representation
En Yu, Zhuoling Li, Shoudong Han +1
Existing online multiple object tracking (MOT) algorithms often consist of two subtasks, detection and re-identification (ReID). In order to enhance the inference speed and reduce…
ANL: Anti-Noise Learning for Cross-Domain Person Re-Identification
Hongliang Zhang, Shoudong Han, Xiaofeng Pan +1
Due to the lack of labels and the domain diversities, it is a challenge to study person re-identification in the cross-domain setting. An admirable method is to optimize the target…
FTN: Foreground-Guided Texture-Focused Person Re-Identification
Donghaisheng Liu, Shoudong Han, Yang Chen +2
Person re-identification (Re-ID) is a challenging task as persons are often in different backgrounds. Most recent Re-ID methods treat the foreground and background information equa…
MAT: Motion-Aware Multi-Object Tracking
Shoudong Han, Piao Huang, Hongwei Wang +4
Modern multi-object tracking (MOT) systems usually model the trajectories by associating per-frame detections. However, when camera motion, fast motion, and occlusion challenges oc…
Refinements in Motion and Appearance for Online Multi-Object Tracking
Piao Huang, Shoudong Han, Jun Zhao +4
Modern multi-object tracking (MOT) system usually involves separated modules, such as motion model for location and appearance model for data association. However, the compatible p…
Poisson Kernel Avoiding Self-Smoothing in Graph Convolutional Networks
Ziqing Yang, Shoudong Han, Jun Zhao
Graph convolutional network (GCN) is now an effective tool to deal with non-Euclidean data, such as social networks in social behavior analysis, molecular structure analysis in the…
AI-GAN: Attack-Inspired Generation of Adversarial Examples
Tao Bai, Jun Zhao, Jinlin Zhu +4
Deep neural networks (DNNs) are vulnerable to adversarial examples, which are crafted by adding imperceptible perturbations to inputs. Recently different attacks and strategies hav…