b'Xiangyu Yue'

DeepAI AI Chat

Featured Co-authors

Dacheng Tao
472 publications
Bo Li
435 publications
Wei Zhang
353 publications
Wei Chen
304 publications
Chang Liu
219 publications
Yu Qiao
211 publications
Trevor Darrell
203 publications
Hongsheng Li
172 publications
Yang Zhang
141 publications
Masayoshi Tomizuka
140 publications
Qian Wang
136 publications

research

∙ 04/28/2023

LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

How to efficiently transform large language models (LLMs) into instructi...

1 Peng Gao, et al. ∙

research

∙ 03/12/2023

Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models

Continual learning (CL) can help pre-trained vision-language models effi...

0 Zangwei Zheng, et al. ∙

research

∙ 08/18/2022

Prompt Vision Transformer for Domain Generalization

Though vision transformers (ViTs) have exhibited impressive ability for ...

0 Zangwei Zheng, et al. ∙

research

∙ 10/27/2021

2nd Place Solution for VisDA 2021 Challenge – Universally Domain Adaptive Image Recognition

The Visual Domain Adaptation (VisDA) 2021 Challenge calls for unsupervis...

0 Haojin Liao, et al. ∙

research

∙ 09/25/2021

Multi-source Few-shot Domain Adaptation

Multi-source Domain Adaptation (MDA) aims to transfer predictive models ...

0 Xiangyu Yue, et al. ∙

research

∙ 09/14/2021

Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data

Background: At the onset of a pandemic, such as COVID-19, data with prop...

21 Hari Prasanna Das, et al. ∙

research

∙ 07/03/2021

Scene-aware Learning Network for Radar Object Detection

Object detection is essential to safe autonomous or assisted driving. Pr...

0 Zangwei Zheng, et al. ∙

research

∙ 06/08/2021

Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets

3D point-clouds and 2D images are different visual representations of th...

4 Chenfeng Xu, et al. ∙

research

∙ 03/23/2021

Self-Supervised Pretraining Improves Self-Supervised Pretraining

While self-supervised pretraining has proven beneficial for many compute...

45 Colorado J. Reed, et al. ∙

research

∙ 11/30/2020

A Customizable Dynamic Scenario Modeling and Data Generation Platform for Autonomous Driving

Safely interacting with humans is a significant challenge for autonomous...

0 Jay Shenoy, et al. ∙

research

∙ 11/25/2020

Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation

Thanks to large-scale labeled training data, deep neural networks (DNNs)...

7 Sicheng Zhao, et al. ∙

research

∙ 11/17/2020

Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources

Sentiment analysis of user-generated reviews or comments on products and...

8 Sicheng Zhao, et al. ∙

research

∙ 10/13/2020

Scenic: A Language for Scenario Specification and Data Generation

We propose a new probabilistic programming language for the design and a...

0 Daniel J. Fremont, et al. ∙

research

∙ 10/02/2020

Pre-Training by Completing Point Clouds

There has recently been a flurry of exciting advances in deep learning m...

1 Hanchen Wang, et al. ∙

research

∙ 09/01/2020

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

Large-scale labeled training datasets have enabled deep neural networks ...

7 Sicheng Zhao, et al. ∙

research

∙ 08/20/2020

Generalizing Fault Detection Against Domain Shifts Using Stratification-Aware Cross-Validation

Incipient anomalies present milder symptoms compared to severe ones, and...

2 Yingshui Tan, et al. ∙

research

∙ 08/20/2020

Using Ensemble Classifiers to Detect Incipient Anomalies

Incipient anomalies present milder symptoms compared to severe ones, and...

5 Baihong Jin, et al. ∙

research

∙ 07/12/2020

Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI

Ensemble learning is widely applied in Machine Learning (ML) to improve ...

9 Yingshui Tan, et al. ∙

research

∙ 03/31/2020

PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation

The requirement of fine-grained perception by autonomous driving systems...

12 Yang Zhang, et al. ∙

research

∙ 10/27/2019

Multi-source Domain Adaptation for Semantic Segmentation

Simulation-to-real domain adaptation for semantic segmentation has been ...

12 Sicheng Zhao, et al. ∙

research

∙ 09/02/2019

Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization without Accessing Target Domain Data

We propose to harness the potential of simulation for the semantic segme...

7 Xiangyu Yue, et al. ∙

research

∙ 11/05/2018

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different d...

0 Spyridon Bakas, et al. ∙

research

∙ 10/11/2018

A Novel Domain Adaptation Framework for Medical Image Segmentation

We propose a segmentation framework that uses deep neural networks and i...

0 Amir Gholami, et al. ∙

research

∙ 09/25/2018

Scenic: Language-Based Scene Generation

Synthetic data has proved increasingly useful in both training and testi...

6 Daniel J. Fremont, et al. ∙

research

∙ 09/22/2018

SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

Earlier work demonstrates the promise of deep-learning-based approaches ...

10 Bichen Wu, et al. ∙

research

∙ 05/17/2018

Counterexample-Guided Data Augmentation

We present a novel framework for augmenting data sets for machine learni...

0 Tommaso Dreossi, et al. ∙

research

∙ 03/31/2018

A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving

3D LiDAR scanners are playing an increasingly important role in autonomo...

0 Xiangyu Yue, et al. ∙

research

∙ 03/23/2018

SqueezeNext: Hardware-Aware Neural Network Design

One of the main barriers for deploying neural networks on embedded syste...

0 Amir Gholami, et al. ∙

research

∙ 11/22/2017

Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions

Neural networks rely on convolutions to aggregate spatial information. H...

0 Bichen Wu, et al. ∙

research

∙ 10/19/2017

SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

In this paper, we address semantic segmentation of road-objects from 3D ...

0 Bichen Wu, et al. ∙