b'Zhi Tian'

research

∙ 07/16/2023

Byzantine-Robust Distributed Online Learning: Taming Adversarial Participants in An Adversarial Environment

This paper studies distributed online learning under Byzantine attacks. ...

0 Xingrong Dong, et al. ∙

research

∙ 06/29/2023

Joint Latency-Energy Minimization for Fog-Assisted Wireless IoT Networks

This work aims to present a joint resource allocation method for a fog-a...

0 Farshad Shams, et al. ∙

research

∙ 10/29/2022

Robust Distributed Learning Against Both Distributional Shifts and Byzantine Attacks

In distributed learning systems, robustness issues may arise from two so...

0 Guanqiang Zhou, et al. ∙

research

∙ 08/08/2022

Two-Stream Networks for Object Segmentation in Videos

Existing matching-based approaches perform video object segmentation (VO...

0 Hannan Lu, et al. ∙

research

∙ 08/04/2022

QC-ODKLA: Quantized and Communication-Censored Online Decentralized Kernel Learning via Linearized ADMM

This paper focuses on online kernel learning over a decentralized networ...

0 Ping Xu, et al. ∙

research

∙ 05/27/2022

Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images

We present a simple yet effective fully convolutional one-stage 3D objec...

0 Zhi Tian, et al. ∙

research

∙ 04/07/2022

Adaptive-Gravity: A Defense Against Adversarial Samples

This paper presents a novel model training solution, denoted as Adaptive...

0 Ali Mirzaeian, et al. ∙

research

∙ 01/19/2022

Poseur: Direct Human Pose Regression with Transformers

We propose a direct, regression-based approach to 2D human pose estimati...

4 Weian Mao, et al. ∙

research

∙ 10/18/2021

BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackers

As a promising distributed learning technology, analog aggregation based...

0 Xin Fan, et al. ∙

research

∙ 05/29/2021

FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutions

We propose a fully convolutional multi-person pose estimation framework ...

0 Weian Mao, et al. ∙

research

∙ 04/28/2021

Twins: Revisiting Spatial Attention Design in Vision Transformers

Very recently, a variety of vision transformer architectures for dense p...

0 Xiangxiang Chu, et al. ∙

research

∙ 04/08/2021

Joint Optimization of Communications and Federated Learning Over the Air

Federated learning (FL) is an attractive paradigm for making use of rich...

0 Xin Fan, et al. ∙

research

∙ 03/30/2021

1-Bit Compressive Sensing for Efficient Federated Learning Over the Air

For distributed learning among collaborative users, this paper develops ...

0 Xin Fan, et al. ∙

research

∙ 03/29/2021

TFPose: Direct Human Pose Estimation with Transformers

We propose a human pose estimation framework that solves the task in the...

0 Weian Mao, et al. ∙

research

∙ 02/22/2021

Do We Really Need Explicit Position Encodings for Vision Transformers?

Almost all visual transformers such as ViT or DeiT rely on predefined po...

0 Xiangxiang Chu, et al. ∙

research

∙ 02/05/2021

Instance and Panoptic Segmentation Using Conditional Convolutions

We propose a simple yet effective framework for instance and panoptic se...

0 Zhi Tian, et al. ∙

research

∙ 12/03/2020

BoxInst: High-Performance Instance Segmentation with Box Annotations

We present a high-performance method that can achieve mask-level instanc...

0 Zhi Tian, et al. ∙

research

∙ 11/19/2020

Unifying Instance and Panoptic Segmentation with Dynamic Rank-1 Convolutions

Recently, fully-convolutional one-stage networks have shown superior per...

0 Hao Chen, et al. ∙

research

∙ 09/18/2020

The Capacity of Multi-user Private Information Retrieval for Computationally Limited Databases

We present a private information retrieval (PIR) scheme that allows a us...

0 William Barnhart, et al. ∙

research

∙ 06/14/2020

FCOS: A simple and strong anchor-free object detector

In computer vision, object detection is one of most important tasks, whi...

17 Zhi Tian, et al. ∙

research

∙ 03/26/2020

Mask Encoding for Single Shot Instance Segmentation

To date, instance segmentation is dominated by twostage methods, as pion...

7 Rufeng Zhang, et al. ∙

research

∙ 03/12/2020

Conditional Convolutions for Instance Segmentation

We propose a simple yet effective instance segmentation framework, terme...

7 Zhi Tian, et al. ∙

research

∙ 02/03/2020

DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data

We present a method for depth estimation with monocular images, which ca...

8 Wei Yin, et al. ∙

research

∙ 01/06/2020

Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation

3D point cloud semantic and instance segmentation is crucial and fundame...

17 Tong He, et al. ∙

research

∙ 01/02/2020

BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation

Instance segmentation is one of the fundamental vision tasks. Recently, ...

29 Hao Chen, et al. ∙

research

∙ 11/18/2019

DirectPose: Direct End-to-End Multi-Person Pose Estimation

We propose the first direct end-to-end multi-person pose estimation fram...

0 Zhi Tian, et al. ∙

research

∙ 10/17/2019

Convolutional Character Networks

Recent progress has been made on developing a unified framework for join...

28 Linjie Xing, et al. ∙

research

∙ 09/15/2019

Communication-Censored Linearized ADMM for Decentralized Consensus Optimization

In this paper, we propose a communication- and computation-efficient alg...

0 Weiyu Li, et al. ∙

research

∙ 06/11/2019

NAS-FCOS: Fast Neural Architecture Search for Object Detection

The success of deep neural networks relies on significant architecture e...

0 Ning Wang, et al. ∙

research

∙ 06/06/2019

A Class of Distributed Event-Triggered Average Consensus Algorithms for Multi-Agent Systems

This paper proposes a class of distributed event-triggered algorithms th...

0 Ping Xu, et al. ∙

research

∙ 04/02/2019

FCOS: Fully Convolutional One-Stage Object Detection

We propose a fully convolutional one-stage object detector (FCOS) to sol...

0 Zhi Tian, et al. ∙

research

∙ 03/12/2019

Knowledge Adaptation for Efficient Semantic Segmentation

Both accuracy and efficiency are of significant importance to the task o...

12 Tong He, et al. ∙

research

∙ 03/05/2019

Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation

Recent semantic segmentation methods exploit encoder-decoder architectur...

1 Zhi Tian, et al. ∙

research

∙ 03/09/2018

Single Shot TextSpotter with Explicit Alignment and Attention

Text detection and recognition in natural images have long been consider...

0 Tong He, et al. ∙

research

∙ 09/12/2016

Detecting Text in Natural Image with Connectionist Text Proposal Network

We propose a novel Connectionist Text Proposal Network (CTPN) that accur...

0 Zhi Tian, et al. ∙

Zhi Tian

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