348 citations · 413 across the 5 of their papers we have counts for
5 papers
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
Yiqun Mei, Yuchen Fan, Yuqian Zhou +3
Deep convolution-based single image super-resolution (SISR) networks embrace the benefits of learning from large-scale external image resources for local recovery, yet most existin…
SkyNet: A Champion Model for DAC-SDC on Low Power Object Detection
Xiaofan Zhang, Cong Hao, Haoming Lu +9
Developing artificial intelligence (AI) at the edge is always challenging, since edge devices have limited computation capability and memory resources but need to meet demanding re…
An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity
Yingzhen Yang, Jiahui Yu, Xingjian Li +2
Regularization of Deep Neural Networks (DNNs) for the sake of improving their generalization capability is important and challenging. The development in this line benefits theoreti…
CCNet: Criss-Cross Attention for Semantic Segmentation
Zilong Huang, Xinggang Wang, Yunchao Wei +4
Contextual information is vital in visual understanding problems, such as semantic segmentation and object detection. We propose a Criss-Cross Network (CCNet) for obtaining full-im…
A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization
Bowen Cheng, Yunchao Wei, Jiahui Yu +5
While training on samples drawn from independent and identical distribution has been a de facto paradigm for optimizing image classification networks, humans learn new concepts in…