activity
20192022
most citedNAT: Neural Architecture Transformer for Accurate and Compact Architectures

72 citations · 117 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV20224 cited

Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images

Bingna Xu, Yong Guo, Luoqian Jiang +2

Deep networks have achieved great success in image rescaling (IR) task that seeks to learn the optimal downscaled representations, i.e., low-resolution (LR) images, to reconstruct…

cs.CV20221 cited

Text-Aware Dual Routing Network for Visual Question Answering

Luoqian Jiang, Yifan He, Jian Chen

Visual question answering (VQA) is a challenging task to provide an accurate natural language answer given an image and a natural language question about the image. It involves mul…

cs.CV2021

Content-Aware Convolutional Neural Networks

Yong Guo, Yaofo Chen, Mingkui Tan +3

Convolutional Neural Networks (CNNs) have achieved great success due to the powerful feature learning ability of convolution layers. Specifically, the standard convolution traverse…

cs.CV20211 cited

Towards Accurate and Compact Architectures via Neural Architecture Transformer

Yong Guo, Yin Zheng, Mingkui Tan +5

Designing effective architectures is one of the key factors behind the success of deep neural networks. Existing deep architectures are either manually designed or automatically se…

cs.CV202035 cited

Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search

Yong Guo, Yaofo Chen, Yin Zheng +4

Neural architecture search (NAS) has become an important approach to automatically find effective architectures. To cover all possible good architectures, we need to search in an e…

cs.CV2020

Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

Yong Guo, Jian Chen, Jingdong Wang +5

Deep neural networks have exhibited promising performance in image super-resolution (SR) by learning a nonlinear mapping function from low-resolution (LR) images to high-resolution…