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20232025
most citedPanoramic Image Inpainting With Gated Convolution And Contextual Reconstruction Loss

7 citations · 8 across the 10 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024

Relevance-guided Audio Visual Fusion for Video Saliency Prediction

Li Yu, Xuanzhe Sun, Pan Gao +1

Audio data, often synchronized with video frames, plays a crucial role in guiding the audience's visual attention. Incorporating audio information into video saliency prediction ta…

cs.CV2024

Multi-task Feature Enhancement Network for No-Reference Image Quality Assessment

Li Yu

Due to the scarcity of labeled samples in Image Quality Assessment (IQA) datasets, numerous recent studies have proposed multi-task based strategies, which explore feature informat…

cs.CV2024★ 1 cited

High-Frequency Enhanced Hybrid Neural Representation for Video Compression

Li Yu, Zhihui Li, Jimin Xiao +1

Neural Representations for Videos (NeRV) have simplified the video codec process and achieved swift decoding speeds by encoding video content into a neural network, presenting a pr…

cs.CV2024

Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling

Di Wu, Shicai Fan, Xue Zhou +4

Reconstruction-based methods have been commonly used for unsupervised anomaly detection, in which a normal image is reconstructed and compared with the given test image to detect a…

eess.IV2024

Joint End-to-End Image Compression and Denoising: Leveraging Contrastive Learning and Multi-Scale Self-ONNs

Yuxin Xie, Li Yu, Farhad Pakdaman +1

Noisy images are a challenge to image compression algorithms due to the inherent difficulty of compressing noise. As noise cannot easily be discerned from image details, such as hi…

eess.IV2024★ 7 cited

Panoramic Image Inpainting With Gated Convolution And Contextual Reconstruction Loss

Li Yu, Yanjun Gao, Farhad Pakdaman +1

Deep learning-based methods have demonstrated encouraging results in tackling the task of panoramic image inpainting. However, it is challenging for existing methods to distinguish…