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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.
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- Pansharpening via Detail Injection Based Convolutional Neural Networks254
This paper designs a new detail injection based convolutional neural network (DiCNN) framework for pansharpening with the MS details being directly formulated in end-to-end manners, where the first detail injections based CNN mines MS details through the PAN image and the MS image, and the second one utilizes only the PAN picture.
- A Real-Time Cross-Modality Correlation Filtering Method for Referring Expression Comprehension253
A novel Realtime Cross-modality Correlation Filtering method (RCCF) that reformulates the referring expression comprehension as a correlation ï¬ltering process and achieves leading performance in RefClef, RefCOCO, Ref COCO+ and RefC OCOg benchmarks.
- Referring Image Segmentation via Cross-Modal Progressive Comprehension250
A Cross-Modal Progressive Comprehension (CMPC) module and a Text-Guided Feature Exchange (TGFE) module to effectively address the challenging task of referring image segmentation.
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- SemanticAdv: Generating Adversarial Examples via Attribute-Conditioned Image Editing150
This paper proposes SemanticAdv to generate a new type of semantically realistic adversarial examples via attribute-conditioned image editing and demonstrates the applicability of SemanticAdv on both face recognition and general street-view images to show its generalization.
- Change detection from synthetic aperture radar images based on neighborhood-based ratio and extreme learning machine145
The experimental results obtained show that the proposed SAR image change detection method is robust to speckle noise and is effective to detect change information among multitemporal SAR images.
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- A Surface Defect Detection Method Based on Positive Samples133
Experiments show that the proposed GAN+LBP algorithm and supervised training algorithm with sufficient training samples have fairly high detection accuracy and because of its unsupervised characteristics, it has higher practical application value.
- TrojDiff: Trojan Attacks on Diffusion Models with Diverse Targets125
An effective Trojan attack against diffusion models, TrojDiff, which optimizes the Trojan diffusion and generative processes during training and achieves high attack performance under different adversarial targets using different types of triggers, while the performance in benign environments is preserved.
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- Multi-attributed heterogeneous graph convolutional network for bot detection95
A novel bot detection framework, namely Bot-AHGCN, is proposed, which models fine-grained network flow objects as a multi-attributed heterogeneous graph and transforms bot detection problem into a semi-supervised node classification task on the graph.
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- Too Far to See? Not Really!—Pedestrian Detection With Scale-Aware Localization Policy88
An active pedestrian detector that explicitly operates over multiple-layer neuronal representations of the input still image and is demonstrated to produce overall lower detection errors on widely used benchmarks, and it works particularly well with far-scale pedestrians.
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- MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs85
This work aims to offer researchers an easy grasp of how to effectively evaluate MLLMs according to different needs and to inspire better evaluation methods, thereby driving the progress of MLLM research.
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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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