His primary scientific interests are in Artificial intelligence, Pattern recognition, Computer vision, Image retrieval and Feature extraction. The study of Artificial intelligence is intertwined with the study of Machine learning in a number of ways. His Pattern recognition research focuses on Object detection and how it relates to Detector, Background subtraction and Segmentation.
As part of the same scientific family, Qi Tian usually focuses on Computer vision, concentrating on Feature vector and intersecting with Salient and Construct. His Image retrieval research integrates issues from Codebook, Quantization, Information retrieval, Search engine indexing and Visualization. His Feature extraction study incorporates themes from Weighting, Motion analysis, Histogram, Key and Robustness.
Artificial intelligence, Pattern recognition, Computer vision, Image retrieval and Machine learning are his primary areas of study. His work on Artificial intelligence deals in particular with Feature extraction, Discriminative model, Feature, Contextual image classification and Visual Word. He has included themes like Visualization and Image in his Pattern recognition study.
His research related to Object detection, Video tracking, Segmentation, Image segmentation and Object might be considered part of Computer vision. He has researched Image retrieval in several fields, including Data mining and Information retrieval, Search engine indexing. His research integrates issues of Representation, Training set and Benchmark in his study of Machine learning.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Machine learning, Computer vision and Discriminative model. His study in Artificial intelligence focuses on Feature, Feature extraction, Feature learning, Benchmark and Deep learning. His research in Feature extraction intersects with topics in Visualization and Convolutional neural network.
Qi Tian interconnects Pixel, Similarity and Quantization in the investigation of issues within Pattern recognition. The various areas that Qi Tian examines in his Machine learning study include Contextual image classification, Sample, Training set and Key. In general Computer vision, his work in Object detection, Image, Moiré pattern and Segmentation is often linked to Domain linking many areas of study.
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Feature extraction, Algorithm and Machine learning. Artificial neural network, Discriminative model, Feature, Convolutional neural network and Benchmark are the core of his Artificial intelligence study. His Pattern recognition research integrates issues from Precision and recall, Image, Object and Pixel.
His research integrates issues of Sequence, Deep learning, Feature learning and Image retrieval in his study of Feature extraction. His Algorithm research includes elements of Sketch and Robustness. His Machine learning research incorporates elements of Image, Probabilistic logic, Similarity and Graph.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Scalable Person Re-identification: A Benchmark
Liang Zheng;Liang Zheng;Liyue Shen;Lu Tian;Shengjin Wang.
international conference on computer vision (2015)
Statistical modeling of complex backgrounds for foreground object detection
Liyuan Li;Weimin Huang;Irene Yu-Hua Gu;Qi Tian.
IEEE Transactions on Image Processing (2004)
Foreground object detection from videos containing complex background
Liyuan Li;Weimin Huang;Irene Y. H. Gu;Qi Tian.
acm multimedia (2003)
Algorithms for subpixel registration
Qi Tian;Michael N Huhns.
Graphical Models /graphical Models and Image Processing /computer Vision, Graphics, and Image Processing (1986)
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
Yifan Sun;Liang Zheng;Yi Yang;Qi Tian.
european conference on computer vision (2018)
MARS: A Video Benchmark for Large-Scale Person Re-Identification
Liang Zheng;Liang Zheng;Zhi Bie;Yifan Sun;Jingdong Wang.
european conference on computer vision (2016)
Pose-Driven Deep Convolutional Model for Person Re-identification
Chi Su;Jianing Li;Shiliang Zhang;Junliang Xing.
international conference on computer vision (2017)
Person Transfer GAN to Bridge Domain Gap for Person Re-identification
Longhui Wei;Shiliang Zhang;Wen Gao;Qi Tian.
computer vision and pattern recognition (2018)
SIFT Meets CNN: A Decade Survey of Instance Retrieval
Liang Zheng;Yi Yang;Qi Tian.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2018)
Deep Attributes Driven Multi-camera Person Re-identification
Chi Su;Shiliang Zhang;Junliang Xing;Wen Gao.
european conference on computer vision (2016)
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