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- Yiwei JiangSuggested from co-authorship
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Works174 from public data
- Depth Matters: Influence of Depth Cues on Visual Saliency297
This work collects a large human eye fixation database compiled from a pool of 600 2D-vs-3D image pairs viewed by 80 subjects, where the depth information is directly provided by the Kinect camera and the eye tracking data are captured in both 2D and 3D free-viewing experiments.
- Collaborative Perception in Autonomous Driving: Methods, Datasets, and Challenges281
This article systematically summarize the collaborative perception methods for ideal scenarios and real-world issues, and highlights gaps and overlooked challenges between current academic research andreal-world applications.
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- Partial Multi-Label Learning by Low-Rank and Sparse Decomposition145
This paper utilizes the low-rank and sparse decomposition scheme and proposes a novel Partial Multi-label Learning by Low-Rank and Sparse decomposition (PML-LRS) approach, which reformulates the observed label set into a label matrix, and decomposes it into a groundtruth label matrix and an irrelevant label matrix.
- GM-PLL: Graph Matching Based Partial Label Learning92
This paper proposes a novel Graph Matching based Partial Label Learning (GM-PLL) framework, where graph Matching scheme is incorporated owing to its excellent capability of exploiting the instance and label relationship, and proposes a relaxed matching prediction model, which can improve the prediction accuracy via GM strategy.
- MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification82
This work proposes an edge features enhancement module to enhance the modality-sharable features in each single-modality space and designs a perceptual edge features (PEF) loss after the edge fusion strategy analysis, which markedly improves the network's performance.
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- Recurrent convolutional network for video-based smoke detection65
This work proposes a novel video-based smoke detection method via Recurrent Neural Networks (RNNs), which first captures the space and motion context information by using deep convolutional motion-space networks and effectively train the smoke model.
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- Salient Object Detection via Low-Rank and Structured Sparse Matrix Decomposition62
In this model, a tree-structured sparsity-inducing norm regularization is firstly introduced to provide a hierarchical description of the image structure to ensure the completeness of the extracted salient object, and high-level priors are integrated to guide the matrix decomposition and enhance the saliency detection.
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- Age Estimation Based on Convolutional Neural Network42
The proposed method uses Convolutional Neural Network CNN to extract facial features and divides different ages into 13 groups and uses the Support Vector Machine SVM classifier to perform the classification.
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- Multi-human Parsing with a Graph-based Generative Adversarial Model27
A novel multi- human parsing model named MH-Parser is introduced, which uses a graph-based generative adversarial model to address the challenges of close-person interaction and occlusion in multi-human parsing.
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- Joint Graph Learning and Matching for Semantic Feature Correspondence25
The graph patterns learnt by the proposed GLAM model are validated to be able to remarkably enhance previous deep graph matching methods by replacing their handcrafted graph structures with the learnt ones.
- Vehicle detection and classification based on convolutional neural network24
This paper extracts visual features from the activation of a deep convolutional network, large-scale sparse learning and other distinguishing features in order to compare their accuracy.
- Multi-task clustering ELM for VIS-NIR cross-modal feature learning21
A multi-task clustering based ELM is proposed to improve the recognition accuracy by learning the shared information between tasks to reduce the obtained cross-modality features.
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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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