83 citations · 196 across the 10 of their papers we have counts for
9 papers · 1 filter
High-Dimensional Noise to Low-Dimensional Manifolds: A Manifold-Space Diffusion Framework for Degraded Hyperspectral Image Classification
Boxiang Yang, Ning Chen, Xia Yue +6
Recently, Hyperspectral Image (HSI) classification has attracted increasing attention in remote sensing. However, HSI data are inherently high-dimensional but low-rank, with discri…
Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution
Ming Cheng, Haoyu Ma, Qiufang Ma +7
Multi-stage strategies are frequently employed in image restoration tasks. While transformer-based methods have exhibited high efficiency in single-image super-resolution tasks, th…
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning
Jialong Wu, Haoyu Ma, Chaoyi Deng +1
Unsupervised pre-training methods utilizing large and diverse datasets have achieved tremendous success across a range of domains. Recent work has investigated such unsupervised pr…
I2F: A Unified Image-to-Feature Approach for Domain Adaptive Semantic Segmentation
Haoyu Ma, Xiangru Lin, Yizhou Yu
Unsupervised domain adaptation (UDA) for semantic segmentation is a promising task freeing people from heavy annotation work. However, domain discrepancies in low-level image stati…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…
Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization
Haoyu Ma, Xiangru Lin, Zifeng Wu +1
Unsupervised domain adaptation (UDA) in semantic segmentation is a fundamental yet promising task relieving the need for laborious annotation works. However, the domain shifts/disc…
Real-MFF: A Large Realistic Multi-focus Image Dataset with Ground Truth
Juncheng Zhang, Qingmin Liao, Shaojun Liu +3
Multi-focus image fusion, a technique to generate an all-in-focus image from two or more partially-focused source images, can benefit many computer vision tasks. However, currently…
An α-Matte Boundary Defocus Model Based Cascaded Network for Multi-focus Image Fusion
Haoyu Ma, Qingmin Liao, Juncheng Zhang +2
Capturing an all-in-focus image with a single camera is difficult since the depth of field of the camera is usually limited. An alternative method to obtain the all-in-focus image…
Boundary Aware Multi-Focus Image Fusion Using Deep Neural Network
Haoyu Ma, Juncheng Zhang, Shaojun Liu +1
Since it is usually difficult to capture an all-in-focus image of a 3D scene directly, various multi-focus image fusion methods are employed to generate it from several images focu…