2 citations · 6 across the 13 of their papers we have counts for
4 papers · 1 filter
Learning Spatially Collaged Fourier Bases for Implicit Neural Representation
Jason Chun Lok Li, Chang Liu, Binxiao Huang +1
Existing approaches to Implicit Neural Representation (INR) can be interpreted as a global scene representation via a linear combination of Fourier bases of different frequencies.…
Hundred-Kilobyte Lookup Tables for Efficient Single-Image Super-Resolution
Binxiao Huang, Jason Chun Lok Li, Jie Ran +4
Conventional super-resolution (SR) schemes make heavy use of convolutional neural networks (CNNs), which involve intensive multiply-accumulate (MAC) operations, and require special…
Lite it fly: An All-Deformable-Butterfly Network
Rui Lin, Jason Chun Lok Li, Jiajun Zhou +3
Most deep neural networks (DNNs) consist fundamentally of convolutional and/or fully connected layers, wherein the linear transform can be cast as the product between a filter matr…
A Spectral Perspective towards Understanding and Improving Adversarial Robustness
Binxiao Huang, Rui Lin, Chaofan Tao +1
Deep neural networks (DNNs) are incredibly vulnerable to crafted, imperceptible adversarial perturbations. While adversarial training (AT) has proven to be an effective defense app…