262 citations · 888 across the 45 of their papers we have counts for
9 papers · 1 filter
Exposure-Referred Signal-to-Noise Ratio for Digital Image Sensors
Abhiram Gnanasambandam, Stanley H. Chan
The signal-to-noise ratio (SNR) is a fundamental tool to measure the performance of an image sensor. However, confusions sometimes arise between the two types of SNRs. The first on…
Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement
Xue Zhang, Gene Cheung, Jiahao Pang +3
A 3D point cloud is typically constructed from depth measurements acquired by sensors at one or more viewpoints. The measurements suffer from both quantization and noise corruption…
Photon Limited Non-Blind Deblurring Using Algorithm Unrolling
Yash Sanghvi, Abhiram Gnanasambandam, Stanley H. Chan
Image deblurring in photon-limited conditions is ubiquitous in a variety of low-light applications such as photography, microscopy, and astronomy. However, the presence of photon s…
Detecting and Segmenting Adversarial Graphics Patterns from Images
Xiangyu Qu, Stanley H. Chan
Adversarial attacks pose a substantial threat to computer vision system security, but the social media industry constantly faces another form of "adversarial attack" in which the h…
Accelerating Atmospheric Turbulence Simulation via Learned Phase-to-Space Transform
Zhiyuan Mao, Nicholas Chimitt, Stanley H. Chan
Fast and accurate simulation of imaging through atmospheric turbulence is essential for developing turbulence mitigation algorithms. Recognizing the limitations of previous approac…
Optical Adversarial Attack
Abhiram Gnanasambandam, Alex M. Sherman, Stanley H. Chan
We introduce OPtical ADversarial attack (OPAD). OPAD is an adversarial attack in the physical space aiming to fool image classifiers without physically touching the objects (e.g.,…
Graph Signal Restoration Using Nested Deep Algorithm Unrolling
Masatoshi Nagahama, Koki Yamada, Yuichi Tanaka +2
Graph signal processing is a ubiquitous task in many applications such as sensor, social, transportation and brain networks, point cloud processing, and graph neural networks. Ofte…
DROID: Driver-centric Risk Object Identification
Chengxi Li, Stanley H. Chan, Yi-Ting Chen
Identification of high-risk driving situations is generally approached through collision risk estimation or accident pattern recognition. In this work, we approach the problem from…
Student-Teacher Learning from Clean Inputs to Noisy Inputs
Guanzhe Hong, Zhiyuan Mao, Xiaojun Lin +1
Feature-based student-teacher learning, a training method that encourages the student's hidden features to mimic those of the teacher network, is empirically successful in transfer…