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- Masaru KitsuregawaSuggested from co-authorship
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Works91 from public data
- CosFace: Large Margin Cosine Loss for Deep Face Recognition3,113
This paper reformulates the softmax loss as a cosine loss by L2 normalizing both features and weight vectors to remove radial variations, based on which acosine margin term is introduced to further maximize the decision margin in the angular space, and achieves minimum intra-class variance and maximum inter- class variance by virtue of normalization and cosine decision margin maximization.
- DiffIR: Efficient Diffusion Model for Image Restoration476
This work proposes an efficient DM for IR (DiffIR), which consists of a compact IR prior extraction network (CPEN), dynamic IR transformer (DIRformer), and denoising network, which can adopt a joint optimization of CPENS2, DIRformer, and denoising network, which can further reduce the estimation error influence.
- FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation156
FreeSeg is proposed, a generic framework to accomplish Unified, Universal and Open-Vocabulary Image Segmentation, which optimizes an all-in-one network via one-shot training and employs the same architecture and parameters to handle diverse segmentation tasks seamlessly in the inference procedure.
- Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition130
A novel approach (namely, Orthogonal Embedding CNNs, or OE-CNNs) is proposed to learn the age-invariant deep face features to reduce the intra-class discrepancy caused by the aging.
- Mobile Edge Computing, Metaverse, 6G Wireless Communications, Artificial Intelligence, and Blockchain: Survey and Their Convergence82
This paper investigates the computational paradigms used to meet the stringent requirements of modern applications of mobile edge computing, and presents the motivation of MEC-based Metaverse and introduces the applications of M EC to the Metaverse.
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- LAPIN: Effective Sequential Pattern Mining Algorithms by Last Position Induction for Dense Databases82
This work proposes a series of novel algorithms, called the LAst Position INduction (LAPIN) sequential pattern mining, which is based on the simple idea that the last position of an item, α is the key to judging whether or not a frequent k-length sequential pattern can be extended to be a frequent (k+1)-length pattern by appending the item α to it.
- Link Based Clustering of Web Search Results81
A new approach to cluster search results returned from Web search engine using link analysis based on common links shared by pages using co-citation and coupling analysis, which is based on document clustering algorithms in IR.
- Evaluating contents-link coupled web page clustering for web search results79
A contents-link coupled clustering algorithm that clusters web pages by combining contents and link analysis is proposed that is effective and promising and applies to cluster web search results.
- Open-Vocabulary Segmentation with Semantic-Assisted Calibration78
This paper studies open-vocabulary segmentation through calibrating in-vocabulary and domain-biased embedding space with generalized contextual prior of CLIP and presents a Semantic-assisted CAlibration Network (SCAN), which achieves state-of-the-art performance on all popular open-vocabulary segmentation benchmarks.
- AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation75
A novel GAN-based anime-face translator, called AniGAN, is proposed to synthesize high-quality anime-faces which are style-consistent with a given reference anime- Face, while preserving the global structure of the source photo-face.
- CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation74
The Layout Designer is introduced, which taps into the potential of large language models in layout planning, transforming them into experts in layout generation and optimization and form CreatiLayout-a systematic solution that integrates the layout model, dataset, and planner for creative layout-to-image generation.
- Global Knowledge Calibration for Fast Open-Vocabulary Segmentation64
A core idea of preserving the generalizable representation when fine-tuning on known classes is proposed, and a text diversification strategy that generates a set of synonyms for each training category is introduced, which prevents the learned representation from collapsing onto specific known category names.
- Toward blockchain and fog computing collaborative design and manufacturing platform: Support customer view60
A blockchain-enabled fog computing-based collaborative design and manufacturing platform is proposed to develop triple communication and cooperation among the manufacturing section, design section, and customers in a trustable environment to improve the data integrity and security problem.
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- A Survey of Mobile Edge Computing for the Metaverse: Architectures, Applications, and Challenges52
This paper proposes a comprehensive survey of the MEC-based Metaverse, and introduces the potential future directions for developing Metaverse systems, e.g., BoundlessXR and CloudXR.
- Human De-occlusion: Invisible Perception and Recovery for Humans48
A two-stage framework is proposed to estimate the invisible portions and recover the content inside of human deocclusion and a stacked network structure is devised to refine inaccurate masks from a general instance segmentation model and predict integrated masks simultaneously.
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- Universal Segmentation at Arbitrary Granularity with Language Instruction47
Unified segmentation model UniLSeg is presented, a universal segmentation model that can perform segmentation at any semantic level with the guidance of language instructions, surpassing both specialist and unified segmentation models.
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- Structured Sparsity Learning for Efficient Video Super-Resolution40
In SSL, a structured pruning scheme called Structured Sparsity Learning (SSL) is developed according to the properties of VSR, which can significantly outperform recent methods quantitatively and qualitatively.
- Basic Binary Convolution Unit for Binarized Image Restoration Network36
This study reconsider components in binary convolution, such as residual connection, BatchNorm, activation function, and structure, for IR tasks, and finds that residual connection can reduce the information loss caused by binarization, and BBCU can serve as a basic unit for binarized IR networks.
- DreamOmni: Unified Image Generation and Editing34
This work introduces DreamOmni, a unified model for image generation and editing that integrates both T2I models and various editing tasks, and develops a synthetic data pipeline using sticker-like elements to synthesize accurate, high-quality datasets efficiently.
- On Combining Link and Contents Information for Web Page Clustering33
The proposed approach automatically clusters the web search results into high quality, semantically meaningful groups in a concise, easy-to-interpret hierarchy with tagging terms and results show that the proposed approach is effective and promising.
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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