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Yichen Guo

5 accepted papers

2026

Burst Image Quality Assessment: A New Benchmark and Unified Framework for Multiple Downstream Tasks

AAAI 2026technical

In recent years, the development of burst imaging technology has improved the capture and processing capabilities of visual data, enabling a wide range of applications. However, the redundancy in burst images leads to the increased storage and transmission demands, as well as reduced efficiency of d

Cited by 0SourcePDFScholar
2023

DINN360: Deformable Invertible Neural Network for Latitude-Aware 360deg Image Rescaling

CVPR 2023poster

With the rapid development of virtual reality, 360deg images have gained increasing popularity. Their wide field of view necessitates high resolution to ensure image quality. This, however, makes it harder to acquire, store and even process such 360deg images. To alleviate this issue, we propose the…

2023

Uncertainty Guided Adaptive Warping for Robust and Efficient Stereo Matching

ICCV 2023poster

Correlation based stereo matching has achieved outstanding performance, which pursues cost volume between two feature maps. Unfortunately, current methods with a fixed trained model do not work uniformly well across various datasets, greatly limiting their real-world applicability. To tackle this is…

Cited by 24PDFScholar
2022

Does Text Attract Attention on E-Commerce Images: A Novel Saliency Prediction Dataset and Method

CVPR 2022poster

E-commerce images are playing a central role in attracting people's attention when retailing and shopping online, and an accurate attention prediction is of significant importance for both customers and retailers, where its research is yet to start. In this paper, we establish the first dataset of s…

Cited by 18PDFcodeScholar
2021

LAU-Net: Latitude Adaptive Upscaling Network for Omnidirectional Image Super-Resolution

CVPR 2021poster

The omnidirectional images (ODIs) are usually at low-resolution, due to the constraints of collection, storage and transmission. The traditional two-dimensional (2D) image super-resolution methods are not effective for spherical ODIs, because ODIs tend to have non-uniformly distributed pixel density…

Cited by 63PDFcodeScholar