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- YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications3,433
This technical report strives to push the YOLO series to the next level, stepping forward with an unwavering mindset for industry application, and builds a suite of deployment-ready networks at various scales to accommodate diversified use cases.
- Towards Discriminability and Diversity: Batch Nuclear-Norm Maximization Under Label Insufficient Situations454
To improve both discriminability and diversity, the proposed Batch Nuclear-norm Maximization (BNM) on the output matrix could boost the learning under typical label insufficient learning scenarios, such as semi-supervised learning, domain adaptation and open domain recognition.
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- Age-Invariant Face Recognition by Multi-Feature Fusionand Decomposition with Self-attention238
A novel Multi-feature Fusion and Decomposition framework for age-invariant face recognition, which learns more discriminative and robust features and reduces the intra-class variants and improves the AIFR performance than previous state-of-the-art methods.
- Parsing-Based View-Aware Embedding Network for Vehicle Re-Identification229
This paper proposes a parsing-based view-aware embedding network (PVEN), which helps capture the stable discriminative information of vehicle under different views and design a common-visible attention to focus on the common visible views, which not only shortens the distance among intra-instances, but also enlarges the discrepancy of inter-instance.
- A Self-Attentive Model with Gate Mechanism for Spoken Language Understanding171
A novel self-attentive model with gate mechanism to fully utilize the semantic correlation between slot and intent and outperforms other popular methods by a large margin in terms of both intent detection error rate and slot filling F1-score is proposed.
- FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset157
FaceVerse is presented, a fine-grained 3D Neural Face Model, which is built from hybrid East Asian face datasets containing 60K fused RGB-D images and 2K high-fidelity 3D head scan models and a novel coarse-to-fine structure is proposed to take better advantage of the hybrid dataset.
- State-Relabeling Adversarial Active Learning150
This paper proposes a state relabeling adversarial active learning model (SRAAL), that leverages both the annotation and the labeled/unlabeled state information for deriving the most informative unlabeled samples.
- Dependency Exploitation: A Unified CNN-RNN Approach for Visual Emotion Recognition135
This paper proposes a unified CNNRNN model to predict the emotion based on the fused features from different levels by exploiting the dependency among them and leverages convolutional neural network with multiple layers to extract different levels of features within a multi-task learning framework.
- A Novel Augmented Reality Navigation System for Endoscopic Sinus and Skull Base Surgery: A Feasibility Study125
It is concluded that this navigational system will provide rhinologists with more intuitive and more detailed imaging information, thus reducing the judgment time and mental workload of surgeons when performing complex sinus and skull base surgeries.
- Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation124
This paper proposes a hierarchical visual-language knowledge distillation method, i.e., Hi-erKD, for open-vocabulary one-stage detection, which significantly surpasses the previous best one- stage detector, and reduces the AP50 performance gap from 14% to 7.3% compared to the best two-stage detector.
- Parallel deblocking filter for HEVC on many‐core processor123
Experiments show that the proposed three-step parallel framework for HEVC dramatically accelerates more than the state-of-the-art parallel method.
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- Let the Data Choose: Flexible and Diverse Anchor Graph Fusion for Scalable Multi-View Clustering101
A novel anchor-based method termed Flexible and Diverse Anchor Graph Fusion for Scalable Multi-view Clustering (FDAGF) and a novel hybrid fusion strategy for multi-size anchor graphs with theoretical proof, which allows flexible and diverse anchor graph fusion.
- Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding98
A novel end-to-end adaptive reconstruction network (ARN) that builds the correspondence between image region proposal and query in an adaptive manner: adaptive grounding and collaborative reconstruction.
- Few Shot Generative Model Adaption via Relaxed Spatial Structural Alignment96
This work proposes a relaxed spatial structural alignment (RSSA) method to calibrate the target generative models during the adaption and designs a cross-domain spatial structural consistency loss comprising the self-correlation and disturbance correlation consistency loss.
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- Efficient parallel HEVC intra‐prediction on many‐core processor90
Experiments show that the proposed method dramatically accelerates more than the state-of-the-art parallel method for HEVC IP.
- Real-World Person Re-Identification via Degradation Invariance Learning84
By introducing a self-supervised disentangled representation learning strategy, this framework is able to simultaneously extract identity-related robust features and remove real-world degradations without extra supervision and is ableTo achieve state-of-the-art performance on several Re-ID benchmarks.
- Symbolic Music Generation with Transformer-GANs83
It is demonstrated via human evaluations and a new discriminative metric that the music generated by the approach outperforms a baseline trained with likelihood maximization, the state-of-the-art Music Transformer, and other GANs used for sequence generation.
- Detection of microplastics in domestic and fetal pigs’ lung tissue in natural environment: A preliminary study75
The presence of MPs in the lung tissue of both domestic and fetal pigs in the natural environment was confirmed, but the main characteristics differed, which indicated the increasing risk of MPs to human respiratory tract is increasing.
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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 2026-10-14. 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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