84 citations · 383 across the 16 of their papers we have counts for
16 papers
CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis
Peng Zhou, Lingxi Xie, Bingbing Ni +1
The style-based GAN (StyleGAN) architecture achieved state-of-the-art results for generating high-quality images, but it lacks explicit and precise control over camera poses. The r…
Learning Cloth Folding Tasks with Refined Flow Based Spatio-Temporal Graphs
Peng Zhou, Omar Zahra, Anqing Duan +3
Cloth folding is a widespread domestic task that is seemingly performed by humans but which is highly challenging for autonomous robots to execute due to the highly deformable natu…
Predicting Quantum Potentials by Deep Neural Network and Metropolis Sampling
Rui Hong, Peng-Fei Zhou, Bin Xi +3
The hybridizations of machine learning and quantum physics have caused essential impacts to the methodology in both fields. Inspired by quantum potential neural network, we here pr…
Preparation of Many-body Ground States by Time Evolution with Variational Microscopic Magnetic Fields and Incomplete Interactions
Ying Lu, Yue-Min Li, Peng-Fei Zhou +1
State preparation is of fundamental importance in quantum physics, which can be realized by constructing the quantum circuit as a unitary that transforms the initial state to the t…
Automatically Differentiable Quantum Circuit for Many-qubit State Preparation
Peng-Fei Zhou, Rui Hong, Shi-Ju Ran
Constructing quantum circuits for efficient state preparation belongs to the central topics in the field of quantum information and computation. As the number of qubits grows fast,…
Deep Video Inpainting Detection
Peng Zhou, Ning Yu, Zuxuan Wu +3
This paper studies video inpainting detection, which localizes an inpainted region in a video both spatially and temporally. In particular, we introduce VIDNet, Video Inpainting De…
FastBERT: a Self-distilling BERT with Adaptive Inference Time
Weijie Liu, Peng Zhou, Zhe Zhao +3
Pre-trained language models like BERT have proven to be highly performant. However, they are often computationally expensive in many practical scenarios, for such heavy models can…
Inclusive GAN: Improving Data and Minority Coverage in Generative Models
Ning Yu, Ke Li, Peng Zhou +3
Generative Adversarial Networks (GANs) have brought about rapid progress towards generating photorealistic images. Yet the equitable allocation of their modeling capacity among sub…
DeepStrip: High Resolution Boundary Refinement
Peng Zhou, Brian Price, Scott Cohen +2
In this paper, we target refining the boundaries in high resolution images given low resolution masks. For memory and computation efficiency, we propose to convert the regions of i…
Reservoir Computing with Planar Nanomagnet Arrays
Peng Zhou, Nathan R. McDonald, Alexander J. Edwards +3
Reservoir computing is an emerging methodology for neuromorphic computing that is especially well-suited for hardware implementations in size, weight, and power (SWaP) constrained…
Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning
Kekai Sheng, Weiming Dong, Menglei Chai +6
Visual aesthetic assessment has been an active research field for decades. Although latest methods have achieved promising performance on benchmark datasets, they typically rely on…
K-BERT: Enabling Language Representation with Knowledge Graph
Weijie Liu, Peng Zhou, Zhe Zhao +4
Pre-trained language representation models, such as BERT, capture a general language representation from large-scale corpora, but lack domain-specific knowledge. When reading a dom…
Sionnx: Automatic Unit Test Generator for ONNX Conformance
Xinli Cai, Peng Zhou, Shuhan Ding +2
Open Neural Network Exchange (ONNX) is an open format to represent AI models and is supported by many machine learning frameworks. While ONNX defines unified and portable computati…
M2KD: Multi-model and Multi-level Knowledge Distillation for Incremental Learning
Peng Zhou, Long Mai, Jianming Zhang +3
Incremental learning targets at achieving good performance on new categories without forgetting old ones. Knowledge distillation has been shown critical in preserving the performan…
Generate, Segment and Refine: Towards Generic Manipulation Segmentation
Peng Zhou, Bor-Chun Chen, Xintong Han +4
Detecting manipulated images has become a significant emerging challenge. The advent of image sharing platforms and the easy availability of advanced photo editing software have re…
Two-Stream Neural Networks for Tampered Face Detection
Peng Zhou, Xintong Han, Vlad I. Morariu +1
We propose a two-stream network for face tampering detection. We train GoogLeNet to detect tampering artifacts in a face classification stream, and train a patch based triplet netw…