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Claim this profileWorks141 from public data
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- Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks479
A new loss function, namely Wing loss, for robust facial landmark localisation with Convolutional Neural Networks (CNNs) is presented, and the superiority of the proposed method over the state-of-the-art approaches is proved.
- The Eighth Visual Object Tracking VOT2020 Challenge Results350
A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in theVDT challenges.
- Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Tracking222
It is demonstrated that the GFS-DCF method is able to significantly improve the performance of a DCF tracker equipped with deep neural network features and enables joint feature selection and filter learning, achieving enhanced discrimination and interpretability of the learned filters.
- MECT: Multi-Metadata Embedding based Cross-Transformer for Chinese Named Entity Recognition143
A novel Multi-metadata Embedding based Cross-Transformer (MECT) to improve the performance of Chinese NER by fusing the structural information of Chinese characters by using multi-metadata embedding in a two-stream Transformer.
- Vision-Based UAV Self-Positioning in Low-Altitude Urban Environments140
A new dataset, DenseUAV, that is the first publicly available dataset tailored for the UAV self-positioning task and incorporates metric learning into representation learning to enhance the model’s discriminative capacity and to reduce the modality discrepancy.
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- The Ninth Visual Object Tracking VOT2021 Challenge Results127
The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative; results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years.
- Dynamic Attention-Controlled Cascaded Shape Regression Exploiting Training Data Augmentation and Fuzzy-Set Sample Weighting105
A new Cascaded Shape Regression architecture, namely Dynamic Attention-Controlled CSR (DAC-CSR), for robust facial landmark detection on unconstrained faces with fault-tolerant mechanism using fuzzy set sample weighting for attention-controlled domain-specific model training.
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- One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusion91
This new paradigm provides strong guidance for unsupervised multimodal fusion without relying on abstract semantics, enhancing task-shared feature learning for broader applicability.
- MFR-DTA: a multi-functional and robust model for predicting drug–target binding affinity and region89
A novel Multi-Functional and Robust Drug–Target binding Affinity prediction (MFR-DTA) method that achieves excellent performance on these datasets, demonstrating its merits and superiority over the state-of-the-art methods.
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- Gaussian mixture 3D morphable face model85
Experiments in fitting the GM-3DMM to 2D face images to facilitate their geometric and photometric normalisation for pose and illumination invariant face recognition demonstrate the merits of the proposed mixture of Gaussians 3D face model.
- MMDG-DTI: Drug–target interaction prediction via multimodal feature fusion and domain generalization80
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- Adaptive Channel Selection for Robust Visual Object Tracking with Discriminative Correlation Filters72
The robustness and stability of the learned appearance model are significantly enhanced by the proposed method as the process of channel selection performs implicit spatial regularisation, using the augmented Lagrangian method to optimise the discriminative filters efficiently.
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- Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild67
This paper investigates the evaluation of dense 3D face reconstruction from a single 2D image in the wild by organising a competition that provides a new benchmark dataset that contains 2000 2D facial images of 135 subjects as well as their 3D ground truth face scans.
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- Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild44
The experimental results obtained on the 300W and Menpo benchmarks demonstrate the superiority of the robust face detection and landmark localisation framework over state-of-the-art methods.
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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