Search Results for author:
Found 13 papers, 5 papers with code
Gait Lateral Network: Learning Discriminative and Compact Representations for Gait Recognition
Gait recognition aims at identifying different people by the walking patterns, which can be conducted at a long distance without the cooperation of subjects.
QAGait: Revisit Gait Recognition from a Quality Perspective
Gait recognition is a promising biometric method that aims to identify pedestrians from their unique walking patterns.
FastPoseGait: A Toolbox and Benchmark for Efficient Pose-based Gait Recognition
Our toolbox supports a set of cutting-edge pose-based gait recognition algorithms and a variety of related benchmarks.
Free Lunch for Gait Recognition: A Novel Relation Descriptor
Gait recognition is to seek correct matches for query individuals by their unique walking patterns.
Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification
Consequently, we propose a cross-modal ordinal pairwise loss to refine the CLIP feature space, where texts and images maintain both semantic alignment and ordering alignment.
Unsupervised Gait Recognition with Selective Fusion
So to make the pre-trained gait recognition model able to be fine-tuned on unlabeled datasets, we propose a new task: Unsupervised Gait Recognition (UGR).
Fine-grained Unsupervised Domain Adaptation for Gait Recognition
Gait recognition has emerged as a promising technique for the long-range retrieval of pedestrians, providing numerous advantages such as accurate identification in challenging conditions and non-intrusiveness, making it highly desirable for improving public safety and security.
An In-Depth Exploration of Person Re-Identification and Gait Recognition in Cloth-Changing Conditions
For the cloth-changing problem, video-based ReID is rarely studied due to the lack of a suitable cloth-changing benchmark, and gait recognition is often researched under controlled conditions.
Dynamic Aggregated Network for Gait Recognition
Specifically, we create a dynamic attention mechanism between the features of neighboring pixels that not only adaptively focuses on key regions but also generates more expressive local motion patterns.
CNTN: Cyclic Noise-tolerant Network for Gait Recognition
Gait recognition aims to identify individuals by recognizing their walking patterns.
Deep Learning-based Occluded Person Re-identification: A Survey
After that, we summarize and compare the performance of recent occluded person Re-ID methods on four popular datasets: Partial-ReID, Partial-iLIDS, Occluded-ReID, and Occluded-DukeMTMC.
Progressive Feature Learning for Realistic Cloth-Changing Gait Recognition
Gait recognition is instrumental in crime prevention and social security, for it can be conducted at a long distance to figure out the identity of persons.
Look and Think Twice: Capturing Top-Down Visual Attention With Feedback Convolutional Neural Networks
While feedforward deep convolutional neural networks (CNNs) have been a great success in computer vision, it is important to remember that the human visual contex contains generally more feedback connections than foward connections.
