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- The Sixth Visual Object Tracking VOT2018 Challenge Results804
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative; results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years.
- The Visual Object Tracking VOT2016 Challenge Results776
The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
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- RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment558
A novel and end-to-end Alignment Generative Adversarial Network (AlignGAN) for the RGB-IR RE-ID task, which consists of a pixel generator, a feature generator and a joint discriminator that is able to not only alleviate the cross-modality and intra- modality variations, but also learn identity-consistent features.
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- Robust Visual Tracking via Structured Multi-Task Sparse Learning427
The results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity.
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- Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer419
This work designs two effective mechanisms including part diversity and part discriminability that can achieve diverse part discovery for occluded person Re-ID in a weakly supervised manner and performs favor-ably against stat-of-the-art methods.
- Cross-Modality Person Re-Identification With Shared-Specific Feature Transfer417
This paper proposes a novel cross-modality shared-specific feature transfer algorithm (termed cm-SSFT) to explore the potential of both the modality-shared information and themodality-specific characteristics to boost the reidentification performance.
- Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification381
This paper proposes to generate cross-modality paired-images and perform both global set-level and fine-grained instance-level alignments for RGB-IR Re-ID and demonstrates that the proposed model favourably against state-of-the-art methods.
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- Geometry Uncertainty Projection Network for Monocular 3D Object Detection316
A GUP Net is proposed to tackle the error amplification problem at both inference and training stages and can infer more reliable object depth than existing methods and outperforms the state-of-the-art image-based monocular 3D detectors.
- Graph Structured Network for Image-Text Matching311
This paper presents a novel Graph Structured Matching Network (GSMN) to learn fine-grained correspondence of structured phrase correspondence, and shows that GSMN outperforms state-of-the-art methods on benchmarks.
- Hi, magic closet, tell me what to wear!290
This paper collects a large clothing What-to-Wear dataset, and thoroughly annotates the whole dataset with 7 multi-value clothing attributes and 10 occasion categories via Amazon Mechanic Turk, to learn a generalize-well model and comprehensively evaluate it.
- Robust Visual Tracking Via Consistent Low-Rank Sparse Learning261
A consistent low-rank sparse tracker that builds upon the particle filter framework for tracking that adaptively prunes and selects candidate particles by using linear sparse combinations of dictionary templates is proposed.
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- Low-Rank Sparse Learning for Robust Visual Tracking254
By representing particles jointly, LRST not only outperforms the state-of-the-art in tracking accuracy but also significantly improves the time complexity of methods that use a similar sparse linear representation model for particles.
- I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs229
This work proposes an end-to-end ZSAR framework based on a structured knowledge graph, which can jointly model the relationships between action-attribute, action-action, and attribute-attribute and designs a novel Two-Stream Graph Convolutional Network (TS-GCN) consisting of a classifier branch and an instance branch.
- Focus Your Attention213
A novel Bidirectional Focal Attention Network (BFAN) is presented, which not only allows to attend to relevant fragments but also diverts all the attention into these relevant fragments to concentrate on them, which enables to avoid preference to long text or complex image.
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- A Keypoint-based Global Association Network for Lane Detection191
A Global Association Network (GANet) is proposed to formulate the lane detection problem from a new perspective, where each keypoint is directly regressed to the starting point of the lane line instead of point-by-point extension, which outperforms previous methods.
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- Life cycle assessment of biodiesel production in China136
This study aims to evaluate energy, economic, and environmental performances of seven categories of biodiesel feedstocks by using the mixed-unit input-output life cycle assessment method, and proposes supporting measures to optimize China's biodiesel development.
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- Cross-Modality Transformer for Visible-Infrared Person Re-Identification105
This work proposes a novel Cross-Modality Trans-former (CMT) to jointly explore a modality-level alignment module and an instance-level module for VI-ReID, the first work to exploit a cross-modality transformer to achieve the modality compensation for VI-ReID.
- Socioeconomic Drivers of Mercury Emissions in China from 1992 to 2007105
Results show that changes in per capita GDP and GDP composition led to increased emissions which offset the reduction of emissions made possible by technology-induced decrease of mercury emissions intensity and changes in final demand mix.
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- Boundary Perception Guidance: A Scribble-Supervised Semantic Segmentation Approach99
This work presents a novel Boundary Perception Guidance approach, which consists of two basic components, i.e. prediction refinement and boundary regression, and employs class-agnostic edge maps for supervision to effectively guide the segmentation network in localizing the boundaries between different semantic regions.
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- Action Unit Memory Network for Weakly Supervised Temporal Action Localization97
This paper presents an Action Unit Memory Network (AUMN) for weakly supervised temporal action localization, which can mitigate the above two challenges by learning an action unit memory bank.
- Cross-modality paired-images generation and augmentation for RGB-infrared person re-identification94
This paper proposes to generate cross-modality paired-images and perform both global set-level and fine-grained instance-level alignments and demonstrates that the proposed model favorably against state-of-the-art methods.
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- System Log Parsing: A Survey85
A comprehensive survey on log parsing is provided as a helpful resource for system administrators and domain experts to choose the most desirable open-source solution or implement new ones based on application-specific requirements.
- Clinical Manifestation and Laboratory Characteristics of SARS-CoV-2 Infection in Pregnant Women85
It is imperative to closely monitor laboratory parameters including the WBC count, LYMPH count, and CRP, along with other imaging features in chest CT scans, to promptly prevent, diagnose, and treat a SARS-CoV-2 infection during pregnancy.
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- Social Event Classification via Boosted Multimodal Supervised Latent Dirichlet Allocation81
The proposed BMM-SLDA can effectively exploit the multimodality and the multiclass property of social events jointly, and make use of the supervised category label information to classify multiclass social event directly, and is suitable for large-scale data analysis by utilizing boosting weighted sampling strategy to iteratively select a small subset of data to efficiently train the corresponding topic models.
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- RankMatch: Exploring the Better Consistency Regularization for Semi-Supervised Semantic Segmentation71
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- Comparisons of four categories of waste recycling in China’s paper industry based on physical input–output life-cycle assessment model70
A physical input-output life-cycle assessment (PIO-LCA) model is used to investigate environmental impacts of four categories of waste recycling in China's paper industry: crop straws, bagasse, textile wastes and scrap paper.
- Waste oil derived biofuels in China bring brightness for global GHG mitigation68
A novel way for global greenhouse gas reduction through reusing China's waste oil to produce biofuels is proposed and measures such as technology innovation, government supervision for waste oil collection and financial subsidies should be introduced to solve bottlenecks.
- Robust Collaborative Learning of Patch-Level and Image-Level Annotations for Diabetic Retinopathy Grading From Fundus Image67
This article presents a robust framework, which collaboratively utilizes patch-level and image-level annotations, for DR severity grading, and proves that the algorithm is robust when facing image quality and distribution variations that commonly exist in real-world practice.
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- Proposal-Based Multiple Instance Learning for Weakly-Supervised Temporal Action Localization65
A novel Proposal-based Multiple Instance Learning (P-MIL) framework that directly classifies the candidate proposals in both the training and testing stages, which includes three key designs: a surrounding contrastive feature extraction module to suppress the discriminative short proposals by considering the surrounding Contrastive information, a proposal completeness evaluation module to inhibit the low-quality proposals with the guidance of the completeness pseudo labels, and an instance-level rank consistency loss.
- Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose Estimation64
A novel Instance-Adaptive and Geometric-Aware Keypoint Learning method for category-level 6D object pose estimation (AG-Pose), which includes two key designs that work together to establish robust keypoint-level correspondences for unseen instances, thus enhancing the generalization ability of the model.
- A Unified Personalized Video Recommendation via Dynamic Recurrent Neural Networks64
The proposed model is designed to exploit video semantic embedding, user interest modeling, and user relevance mining jointly to model users' preferences and becomes an interest network which can capture users' high level interests effectively.
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- Latent Support Vector Machine Modeling for Sign Language Recognition with Kinect62
A novel algorithm to model and recognize sign language performed in front of a Microsoft Kinect sensor is proposed that first assigns a binary latent variable to each frame in training videos for indicating its discriminative capability, then develops a latent support vector machine model to classify the signs.
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- Multi-modal Multi-view Topic-opinion Mining for Social Event Analysis57
The proposed MMTOM is able to not only discover multi-modal common topics from all collections as well as summarize the similarities and differences of these collections along each specific topic, but also automatically mine multi-view opinions on the learned topics across different collections.
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- Unintended consequences of bioethanol feedstock choice in China56
Cellulose-based feedstocks in general showed positive economic, energy, and environmental performance; but may lead to increasing negative impacts on freshwater use, global warming, toxicity, and aquatic ecotoxicity.
- Life-Cycle Implications of Using Crop Residues for Various Energy Demands in China55
Hybrid life-cycle environmental and economic analyses evaluate and compare the atmospheric chemical, climatic, ecological, and economic issues associated with a set of energy conversion technologies that use crop residues for various energy demands in China to show that the return of crop residues to the fields, silo/amination and anaerobic digestion offer the greatest ecological benefits.
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- Recent advances in 2D MXene-based heterostructures for gas sensing: mechanisms and applications in environmental and biomedical fields50
This review evaluates the latest advancements in MXene-based gas sensors, evaluating the proposed mechanisms for detecting common volatile organic compounds such as acetone, formaldehyde, ethanol, ammonia, and nitrogen oxides and the current limitations and prospective research avenues concerning the utilization of MXenes.
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- Adaptive Spot-Guided Transformer for Consistent Local Feature Matching48
This work proposes Adaptive Spot-Guided Transformer for local feature matching (ASTR), which jointly models the local consistency and scale variations in a unified coarse-to-fine architecture.
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- Learning Hierarchical Visual Transformation for Domain Generalizable Visual Matching and Recognition45
An effective Hierarchical Visual Transformation network is proposed to be extended as EHVT, which helps the model to effectively learn domain-invariant representation and narrow the domain gap in various visual matching and recognition tasks, such as stereo matching, pedestrian retrieval, and image classification.
- Adaptive Agent Transformer for Few-Shot Segmentation44
A novel end-to-end adaptive agent transformer (AAFormer) is proposed to integrate prototypical and affinity learning to exploit the complementarity between them via a transformer encoder-decoder architecture, including a representation encoder, an agent learning decoder and an agent matching decoder.
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- A Structured Graph Attention Network for Vehicle Re-Identification44
A Structured Graph ATtention network (SGAT) is proposed to fully exploit these relationships and allow the message propagation to update the features of graph nodes and achieve significant improvements over the state-of-the-art methods.
- Alginate/gelatin-based hybrid hydrogels with function of injecting and encapsulating cells in situ43
A hybrid hydrogel consisting of alginate, gelatin, and polyacrylamide was constructed with the combination of advantages of natural and synthetic polymers, showing higher mechanical tensile strength at lower pH and good resilience and toughness.
- Fabrication of Hydrogel with Cell Adhesive Micropatterns for Mimicking the Oriented Tumor-Associated Extracellular Matrix43
For mimicking the fibrous extracellular matrix (ECM), a facile method for patterning anticell adhesive substrate was novelly applied on agarose hydrogel and could actually influence behaviors of different cancer cells, including adhesion, growth, and migration.
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- Joint Attention-Guided Feature Fusion Network for Saliency Detection of Surface Defects39
A joint attention-guided feature fusion network (JAFFNet) for saliency detection of surface defects based on the encoder–decoder network that learns to emphasize defect features and suppress background noise during feature fusion, which is beneficial for detecting low-contrast defects.
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- ROML: A Robust Feature Correspondence Approach for Matching Objects in A Set of Images37
This work considers simultaneously matching object instances in a set of images, where both inlier and outlier features are extracted, and proposes a novel framework, termed Robust Object Matching using Low-rank constraint (ROML), to address this problem.
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- Evaluation of major polluting accidents in China—Results and perspectives36
A summary evaluation on the major polluting events in China from 2002 to 2006 is presented and some basic lessons drawn shown are shown.
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- Boosted multi-class semi-supervised learning for human action recognition35
A boosted multi-class semi-supervised learning algorithm in which the co-EM algorithm is adopted to leverage the information from unlabeled data to deal with the insufficient labeled data and high computational expense is proposed.
- How Much Will China Weigh? Perspectives from Consumption Structure and Technology Development35
The results provide a foundation for quantitative studies of resource consumption and waste generation in China, which given its increasing pivotal role in manufacturing is also helpful for research on the material metabolism of the entire world.
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- Reutilisation-extended material flows and circular economy in China34
Interpretations of resource reutilisation-related laws and regulations of CE and the corresponding policy suggestions are proposed based on the results.
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- Expression of selenocysteine-containing glutathione S-transferase in Escherichia coli32
It is concluded that introduction of a selenocysteine residue into the catalytic site of a glutathione S-transferase is not sufficient to induce GPX activity in spite of a maintained glutathion-binding capacity and that recombinant selenoproteins with internal selencysteine residues may be heterologously produced in E. coli.
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- Appearance Prompt Vision Transformer for Connectome Reconstruction19
A coherent and unified Appearance Prompt Vision Transformer is proposed to integrate affinity and metric learning to exploit the complementarity by learning long-range spatial dependencies and achieves consistent improvements with huge flexibility under the same post-processing strategy.
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- Electron Microscopy Images as Set of Fragments for Mitochondrial Segmentation12
This paper designs a coherent fragment vision transformer (FragViT) combined with affinity learning to manipulate features on 3D fragments yet explore mutual relationships to model fragment-wise context, enjoying locality prior without sacrificing global reception.
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- Not Every Side Is Equal: Localization Uncertainty Estimation for Semi-Supervised 3D Object Detection10
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- Structure-Aware Correspondence Learning for Relative Pose Estimation3
A novel Structure-Aware Correspondence Learning method for Relative Pose Estimation, which consists of two key modules that can naturally estimate 3D-3D correspondences for unseen objects without explicit feature matching for precise relative pose estimation.
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- Occlusion Detection via Structured Sparse Learning for Robust Object Tracking1
A novel tracking algorithm that models and detects occlusion through structured sparse learning is proposed and extensive experimental results show that the proposed tracker consistently outperforms the state-of-the-art trackers.
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- Learning semantic topics for domain-adapted textual knowledge transfer–
This work calculates the topic similarity between source and target domain, which is severed as an effective constraint to regularize the training process and hence improve the generalization of the source model to the target domain.
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- Simulation of the velocity and temperature distribution in Huabei-type multi-span plastic greenhouse–
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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 2026-10-13. 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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