93 citations · 390 across the 47 of their papers we have counts for
9 papers · 1 filter
Onsite Non-Line-of-Sight Imaging via Online Calibrations
Zhengqing Pan, Ruiqian Li, Tian Gao +6
There has been an increasing interest in deploying non-line-of-sight (NLOS) imaging systems for recovering objects behind an obstacle. Existing solutions generally pre-calibrate th…
Pre-trained Gaussian Processes for Bayesian Optimization
Zi Wang, George E. Dahl, Kevin Swersky +5
Bayesian optimization (BO) has become a popular strategy for global optimization of expensive real-world functions. Contrary to a common expectation that BO is suited to optimizing…
Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model
Zi Wang
Knowledge distillation (KD) is a successful approach for deep neural network acceleration, with which a compact network (student) is trained by mimicking the softmax output of a pr…
Acoustic-based Object Detection for Pedestrian Using Smartphone
Zi Wang, Jie Yang
Walking while using a smartphone is becoming a major pedestrian safety concern as people may unknowingly bump into various obstacles that could lead to severe injuries. In this pap…
Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis
Zi Wang
Knowledge distillation (KD) has proved to be an effective approach for deep neural network compression, which learns a compact network (student) by transferring the knowledge from…
Convolutional Neural Network Pruning with Structural Redundancy Reduction
Zi Wang, Chengcheng Li, Xiangyang Wang
Convolutional neural network (CNN) pruning has become one of the most successful network compression approaches in recent years. Existing works on network pruning usually focus on…
XCloud-pFISTA: A Medical Intelligence Cloud for Accelerated MRI
Yirong Zhou, Chen Qian, Yi Guo +6
Machine learning and artificial intelligence have shown remarkable performance in accelerated magnetic resonance imaging (MRI). Cloud computing technologies have great advantages i…
Exploring Adversarial Robustness of Deep Metric Learning
Thomas Kobber Panum, Zi Wang, Pengyu Kan +2
Deep Metric Learning (DML), a widely-used technique, involves learning a distance metric between pairs of samples. DML uses deep neural architectures to learn semantic embeddings o…
Non-line-of-Sight Imaging via Neural Transient Fields
Siyuan Shen, Zi Wang, Ping Liu +5
We present a neural modeling framework for Non-Line-of-Sight (NLOS) imaging. Previous solutions have sought to explicitly recover the 3D geometry (e.g., as point clouds) or voxel d…