Jia Wan

IEEE Trans. Pattern Anal. Mach. Intell., May, 2024

Robust Unsupervised Crowd Counting and Localization with Adaptive Resolution SAM.

[BibT_eX]

[DOI]

CoRR, 2024

Robust Zero-Shot Crowd Counting and Localization With Adaptive Resolution SAM.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Modeling Noisy Annotations for Point-Wise Supervision.

[BibT_eX]

[DOI]

Qiangqiang Wu

Norbert Scherer-Negenborn

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

The First Visual Object Tracking Segmentation VOTS2023 Challenge Results.

[BibT_eX]

[DOI]

Kannappan Palaniappan

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Weakly-Supervised Scene-Specific Crowd Counting Using Real-Synthetic Hybrid Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

On Diversity in Image Captioning: Metrics and Methods.

[BibT_eX]

[DOI]

Qingzhong Wang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Kernel-Based Density Map Generation for Dense Object Counting.

[BibT_eX]

[DOI]

Qingzhong Wang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Crowd Counting in the Frequency Domain.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Angular-Driven Feedback Restoration Networks for Imperfect Sketch Recognition.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2021

Fine-Grained Crowd Counting.

[BibT_eX]

[DOI]

Nikil Senthil Kumar

IEEE Trans. Image Process., 2021

The Implicit Biases of Stochastic Gradient Descent on Deep Neural Networks with Batch Normalization.

[BibT_eX]

[DOI]

CoRR, 2021

Dynamic Momentum Adaptation for Zero-Shot Cross-Domain Crowd Counting.

[BibT_eX]

[DOI]

Qiangqiang Wu

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Progressive Unsupervised Learning for Visual Object Tracking.

[BibT_eX]

[DOI]

Qiangqiang Wu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

A Generalized Loss Function for Crowd Counting and Localization.

[BibT_eX]

[DOI]

Ziquan Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Modeling Noisy Annotations for Crowd Counting.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Robust Hierarchical Deep Learning for Vehicular Management.

[BibT_eX]

[DOI]

Xuelong Li

IEEE Trans. Veh. Technol., 2019

Hierarchical Feature Selection for Random Projection.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2019

Adaptive Density Map Generation for Crowd Counting.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Residual Regression With Semantic Prior for Crowd Counting.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Deep Metric Learning for Crowdedness Regression.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. Video Technol., 2018

Locality constraint distance metric learning for traffic congestion detection.

[BibT_eX]

[DOI]

Pattern Recognit., 2018

2017

Traffic congestion analysis: A new Perspective.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

Congested scene classification via efficient unsupervised feature learning and density estimation.

[BibT_eX]

[DOI]