Search Results for author: Tianyu Zhang

Found 16 papers, 7 papers with code

FQ-ViT: Fully Quantized Vision Transformer without Retraining

1 code implementation27 Nov 2021 Yang Lin, Tianyu Zhang, Peiqin Sun, Zheng Li, Shuchang Zhou

In this work, we present a systematic method to reduce the performance degradation and inference complexity of Quantized Transformers.


On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure

no code implementations5 May 2021 Yunhua Xiang, Tianyu Zhang, Xu Wang, Ali Shojaie, Noah Simon

Originally developed for imputing missing entries in low rank, or approximately low rank matrices, matrix completion has proven widely effective in many problems where there is no reason to assume low-dimensional linear structure in the underlying matrix, as would be imposed by rank constraints.

Matrix Completion

Ternary Hashing

no code implementations16 Mar 2021 Chang Liu, Lixin Fan, Kam Woh Ng, Yilun Jin, Ce Ju, Tianyu Zhang, Chee Seng Chan, Qiang Yang

This paper proposes a novel ternary hash encoding for learning to hash methods, which provides a principled more efficient coding scheme with performances better than those of the state-of-the-art binary hashing counterparts.

Learning Contextualized Knowledge Graph Structures for Commonsense Reasoning

no code implementations1 Jan 2021 Jun Yan, Mrigank Raman, Tianyu Zhang, Ryan Rossi, Handong Zhao, Sungchul Kim, Nedim Lipka, Xiang Ren

Recently, neural-symbolic architectures have achieved success on commonsense reasoning through effectively encoding relational structures retrieved from external knowledge graphs (KGs) and obtained state-of-the-art results in tasks such as (commonsense) question answering and natural language inference.

Knowledge Graphs Natural Language Inference +1

UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identification

1 code implementation CVPR 2021 Tianyu Zhang, Lingxi Xie, Longhui Wei, Zijie Zhuang, Yongfei Zhang, Bo Li, Qi Tian

The main difficulty of person re-identification (ReID) lies in collecting annotated data and transferring the model across different domains.

Domain Adaptation Image Generation +1

A robust solution of a statistical inverse problem in multiscale computational mechanics using an artificial neural network

no code implementations16 Nov 2020 Florent Pled, Christophe Desceliers, Tianyu Zhang

An initial database made up with input and target data is first generated from the computational model, from which a processed database is deduced by conditioning the input data with respect to the target data using the nonparametric statistics.

Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks

no code implementations20 Jun 2020 Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang

This paper investigates capabilities of Privacy-Preserving Deep Learning (PPDL) mechanisms against various forms of privacy attacks.

Privacy Preserving Deep Learning

Neural Networks Weights Quantization: Target None-retraining Ternary (TNT)

no code implementations18 Dec 2019 Tianyu Zhang, Lei Zhu, Qian Zhao, Kilho Shin

Quantization of weights of deep neural networks (DNN) has proven to be an effective solution for the purpose of implementing DNNs on edge devices such as mobiles, ASICs and FPGAs, because they have no sufficient resources to support computation involving millions of high precision weights and multiply-accumulate operations.


Background Segmentation for Vehicle Re-Identification

no code implementations15 Oct 2019 Mingjie Wu, Yongfei Zhang, Tianyu Zhang, Wen-qi Zhang

Vehicle re-identification (Re-ID) is very important in intelligent transportation and video surveillance. Prior works focus on extracting discriminative features from visual appearance of vehicles or using visual-spatio-temporal information. However, background interference in vehicle re-identification have not been explored. In the actual large-scale spatio-temporal scenes, the same vehicle usually appears in different backgrounds while different vehicles might appear in the same background, which will seriously affect the re-identification performance.

Vehicle Re-Identification

Single Camera Training for Person Re-identification

1 code implementation24 Sep 2019 Tianyu Zhang, Lingxi Xie, Longhui Wei, Yongfei Zhang, Bo Li, Qi Tian

Differently, this paper investigates ReID in an unexplored single-camera-training (SCT) setting, where each person in the training set appears in only one camera.

Metric Learning Person Re-Identification

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