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- Xinchao WangSuggested from co-authorship
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Works19 from public data
- Occlusion-Embedded Hybrid Transformer for Light Field Super-Resolution41
This hybrid network combines the strengths of convolutional networks and Transformers via spatial-angular separable convolution (SASep-Conv) and angular self-attention (ASA) and allows OHT to capture global angular correlations effectively.
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- Exploiting Blurry Representations for Event-guided Video Super-Resolution3
BluR-EVSR is proposed, a unified framework that implicitly models Blurry Representations and leverages Event cameras to jointly address both blur and resolution degradation for VSR, and significantly outperforms prior BVSR and event-based approaches.
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- AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results3
This paper thoroughly evaluates the state-of-the-art advances in high-FPS single image motion deblurring, showcasing the significant progress in the field, while leveraging samples of the novel dataset, MIORe, that introduces challenging examples of movement patterns.
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- Asymmetric Dual-Lens Video Deblurring2
This paper proposes a practical video deblurring method, AsLeD-Net, which recurrently aligns and propagates temporal reference features from ultra-wide views fused with features extracted from wide-angle blurry frames, and validate the effectiveness of AsLeD-Net through extensive experiments.
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- Enhancing sparse multi-view super-resolution with unified multi-plane image spatial representation1
A novel sparse multi-view SR framework based on a unified spatial representation reference is proposed, which computes a multi-plane image spatial representation from the multi-view images and has spatial perception.
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- Event-Guided Scene Text Image Super-Resolution–
The core of EvTSR is the dual-stream frequency boost mechanism, which separates image features into high- and low-frequency components, and the cross-modal fusion mechanism, which effectively aligns event and image features, enabling robust information fusion.
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- FreLay: Frequency-aware Energy Function for Training-free Layout-to-Image Generation–
This paper introduces FreLay, a novel training-free approach equipped with a frequency-aware energy function that consistently outperforms existing state-of-the-art training-free methods both qualitatively and quantitatively across multiple datasets.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-11. 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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