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- Stan Ziqing LiSuggested from co-authorship
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Works154 from public data
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- Learning Multi-scale Block Local Binary Patterns for Face Recognition682
Experiments on Face Recognition Grand Challenge (FRGC) ver2.0 database show that the proposed MB-LBP method significantly outperforms other LBP based face recognition algorithms.
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- The Visual Object Tracking VOT2014 Challenge Results588
The Visual Object Tracking challenge 2014, VOT2014, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance and introduces a new dataset with full annotation of targets by rotated bounding boxes and per-frame attribute.
- Salient Color Names for Person Re-identification550
This paper proposes a novel salient color names based color descriptor (SCNCD) to describe colors that outperforms the state-of-the-art performance (without user’s feedback optimization) on two challenging datasets (VIPeR and PRID 450S).
- Face Detection Based on Multi-Block LBP Representation447
This paper presents the use of a new set of distinctive rectangle features, called Multi-block Local Binary Patterns (MB-LBP), for face detection, which encodes rectangular regions' intensities by local binary pattern operator, and the resulting binary patterns can describe diverse local structures of images.
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- Embedding Deep Metric for Person Re-identification: A Study Against Large Variations313
A novel moderate positive sample mining method to train robust CNN for person re-identification, dealing with the problem of large variation is proposed and the learning by a metric weight constraint is improved, so that the learned metric has a better generalization ability.
- Partial Face Recognition: Alignment-Free Approach313
An alignment-free face representation method based on Multi-Keypoint Descriptors (MKD), where the descriptor size of a face is determined by the actual content of the image, which is superior in recognizing both holistic and partial faces without requiring alignment.
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- A Fast and Accurate Unconstrained Face Detector294
A new image feature called Normalized Pixel Difference (NPD) is proposed, computed as the difference to sum ratio between two pixel values, inspired by the Weber Fraction in experimental psychology, which is scale invariant, bounded, and able to reconstruct the original image.
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- Learning Efficient Single-Stage Pedestrian Detectors by Asymptotic Localization Fitting256
An efficient single-stage pedestrian detection architecture (denoted as ALFNet) is designed, achieving state-of-the-art performance on CityPersons and Caltech, two of the largest pedestrian detection benchmarks, and hence resulting in an attractive pedestrian detector in both accuracy and speed.
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- Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification186
A Noise Resistible Mutual-Training (NRMT) method, which maintains two networks during training to perform collaborative clustering and mutual instance selection, which outperforms the state-of-the-art UDA methods for person re-ID.
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- Vehicle Re-Identification Using Quadruple Directional Deep Learning Features158
The proposed QD-DLF approach outperforms multiple state-of-the-art vehicle re-identification methods and is applicable to both VeRi and VehicleID databases.
- Heterogeneous Face Recognition from Local Structures of Normalized Appearance149
MB-LBP, an extension of LBP operator, is applied to encode the local image structures in the transformed domain, and further learn the most discriminant local features for recognition in heterogeneous face images.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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