activity
20172020
most citedWhen Unsupervised Domain Adaptation Meets Tensor Representations

25 citations · 52 across the 4 of their papers we have counts for

collaborators

7 papers

eess.IV20201 cited

NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image

Boaz Arad, Radu Timofte, Ohad Ben-Shahar +4

This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. As…

eess.IV201919 cited

AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results

Kai Zhang, Shuhang Gu, Radu Timofte +26

This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Takin…

cs.CV2018

Towards Effective Deep Embedding for Zero-Shot Learning

Lei Zhang, Peng Wang, Lingqiao Liu +4

Zero-shot learning (ZSL) can be formulated as a cross-domain matching problem: after being projected into a joint embedding space, a visual sample will match against all candidate…

cs.CV2018

Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network

Lei Zhang, Peng Wang, Chunhua Shen +4

Deep neural networks have achieved remarkable success in single image super-resolution (SISR). The computing and memory requirements of these methods have hindered their applicatio…

cs.CV2018

Accurate Spectral Super-resolution from Single RGB Image Using Multi-scale CNN

Yiqi Yan, Lei Zhang, Jun Li +2

Different from traditional hyperspectral super-resolution approaches that focus on improving the spatial resolution, spectral super-resolution aims at producing a high-resolution h…

cs.CV20177 cited

Beyond Low Rank: A Data-Adaptive Tensor Completion Method

Lei Zhang, Wei Wei, Qinfeng Shi +3

Low rank tensor representation underpins much of recent progress in tensor completion. In real applications, however, this approach is confronted with two challenging problems, nam…