33 citations · 53 across the 11 of their papers we have counts for
11 papers
Gabor is Enough: Interpretable Deep Denoising with a Gabor Synthesis Dictionary Prior
Nikola Janjušević, Amirhossein Khalilian-Gourtani, Yao Wang
Image processing neural networks, natural and artificial, have a long history with orientation-selectivity, often described mathematically as Gabor filters. Gabor-like filters have…
FS6D: Few-Shot 6D Pose Estimation of Novel Objects
Yisheng He, Yao Wang, Haoqiang Fan +2
6D object pose estimation networks are limited in their capability to scale to large numbers of object instances due to the close-set assumption and their reliance on high-fidelity…
CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing
Nikola Janjušević, Amirhossein Khalilian-Gourtani, Yao Wang
Deep learning based methods hold state-of-the-art results in low-level image processing tasks, but remain difficult to interpret due to their black-box construction. Unrolled optim…
Domain Adaptation of Networks for Camera Pose Estimation: Learning Camera Pose Estimation Without Pose Labels
Jack Langerman, Ziming Qiu, Gábor Sörös +3
One of the key criticisms of deep learning is that large amounts of expensive and difficult-to-acquire training data are required in order to train models with high performance and…
Nyström Regularization for Time Series Forecasting
Zirui Sun, Mingwei Dai, Yao Wang +1
This paper focuses on learning rate analysis of Nyström regularization with sequential sub-sampling for -mixing time series. Using a recently developed Banach-valued Bernstein i…
Generalization Performance of Empirical Risk Minimization on Over-parameterized Deep ReLU Nets
Shao-Bo Lin, Yao Wang, Ding-Xuan Zhou
In this paper, we study the generalization performance of global minima for implementing empirical risk minimization (ERM) on over-parameterized deep ReLU nets. Using a novel deepe…