Search Results for author: Xin Ye

Found 23 papers, 4 papers with code

AdaWM: Adaptive World Model based Planning for Autonomous Driving

no code implementations22 Jan 2025 Hang Wang, Xin Ye, Feng Tao, Chenbin Pan, Abhirup Mallik, Burhaneddin Yaman, Liu Ren, Junshan Zhang

World model based reinforcement learning (RL) has emerged as a promising approach for autonomous driving, which learns a latent dynamics model and uses it to train a planning policy.

Autonomous Driving Model-based Reinforcement Learning +1

Efficient MedSAMs: Segment Anything in Medical Images on Laptop

1 code implementation20 Dec 2024 Jun Ma, Feifei Li, Sumin Kim, Reza Asakereh, Bao-Hiep Le, Dang-Khoa Nguyen-Vu, Alexander Pfefferle, Muxin Wei, Ruochen Gao, Donghang Lyu, Songxiao Yang, Lennart Purucker, Zdravko Marinov, Marius Staring, Haisheng Lu, Thuy Thanh Dao, Xincheng Ye, Zhi Li, Gianluca Brugnara, Philipp Vollmuth, Martha Foltyn-Dumitru, Jaeyoung Cho, Mustafa Ahmed Mahmutoglu, Martin Bendszus, Irada Pflüger, Aditya Rastogi, Dong Ni, Xin Yang, Guang-Quan Zhou, Kaini Wang, Nicholas Heller, Nikolaos Papanikolopoulos, Christopher Weight, Yubing Tong, Jayaram K Udupa, Cahill J. Patrick, Yaqi Wang, Yifan Zhang, Francisco Contijoch, Elliot McVeigh, Xin Ye, Shucheng He, Robert Haase, Thomas Pinetz, Alexander Radbruch, Inga Krause, Erich Kobler, Jian He, Yucheng Tang, Haichun Yang, Yuankai Huo, Gongning Luo, Kaisar Kushibar, Jandos Amankulov, Dias Toleshbayev, Amangeldi Mukhamejan, Jan Egger, Antonio Pepe, Christina Gsaxner, Gijs Luijten, Shohei Fujita, Tomohiro Kikuchi, Benedikt Wiestler, Jan S. Kirschke, Ezequiel de la Rosa, Federico Bolelli, Luca Lumetti, Costantino Grana, Kunpeng Xie, Guomin Wu, Behrus Puladi, Carlos Martín-Isla, Karim Lekadir, Victor M. Campello, Wei Shao, Wayne Brisbane, Hongxu Jiang, Hao Wei, Wu Yuan, Shuangle Li, Yuyin Zhou, Bo wang

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice.

Image Segmentation Medical Image Segmentation +2

Adaptive Model Predictive Control for Differential-Algebraic Systems towards a Higher Path Accuracy for Physically Coupled Robots

no code implementations4 Dec 2024 Xin Ye, Karl Handwerker, Sören Hohmann

The physical coupling between robots has the potential to improve the capabilities of multi-robot systems in challenging manufacturing processes.

Model Predictive Control

MTA: Multimodal Task Alignment for BEV Perception and Captioning

no code implementations16 Nov 2024 Yunsheng Ma, Burhaneddin Yaman, Xin Ye, Feng Tao, Abhirup Mallik, Ziran Wang, Liu Ren

Bird's eye view (BEV)-based 3D perception plays a crucial role in autonomous driving applications.

Autonomous Driving

Temporal Scaling Law for Large Language Models

no code implementations27 Apr 2024 Yizhe Xiong, Xiansheng Chen, Xin Ye, Hui Chen, Zijia Lin, Haoran Lian, Zhenpeng Su, Wei Huang, Jianwei Niu, Jungong Han, Guiguang Ding

In this paper, we propose the novel concept of Temporal Scaling Law, studying how the test loss of an LLM evolves as the training steps scale up.

Position

LORD: Large Models based Opposite Reward Design for Autonomous Driving

no code implementations27 Mar 2024 Xin Ye, Feng Tao, Abhirup Mallik, Burhaneddin Yaman, Liu Ren

Recently, large pretrained models have gained significant attention as zero-shot reward models for tasks specified with desired linguistic goals.

Autonomous Driving Imitation Learning +1

MGTR: Multi-Granular Transformer for Motion Prediction with LiDAR

no code implementations5 Dec 2023 Yiqian Gan, Hao Xiao, Yizhe Zhao, Ethan Zhang, Zhe Huang, Xin Ye, Lingting Ge

Motion prediction has been an essential component of autonomous driving systems since it handles highly uncertain and complex scenarios involving moving agents of different types.

Autonomous Driving Decoder +2

PMP-Swin: Multi-Scale Patch Message Passing Swin Transformer for Retinal Disease Classification

no code implementations20 Nov 2023 Zhihan Yang, Zhiming Cheng, Tengjin Weng, Shucheng He, Yaqi Wang, Xin Ye, Shuai Wang

Specifically, we design a Patch Message Passing (PMP) module based on the Message Passing mechanism to establish global interaction for pathological semantic features and to exploit the subtle differences further between different diseases.

Multi-class Classification

Speech2Slot: An End-to-End Knowledge-based Slot Filling from Speech

no code implementations10 May 2021 Pengwei Wang, Xin Ye, Xiaohuan Zhou, Jinghui Xie, Hao Wang

In contrast to conventional pipeline Spoken Language Understanding (SLU) which consists of automatic speech recognition (ASR) and natural language understanding (NLU), end-to-end SLU infers the semantic meaning directly from speech and overcomes the error propagation caused by ASR.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +8

Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph

1 code implementation CVPR 2021 Xin Ye, Yezhou Yang

We present a novel two-layer hierarchical reinforcement learning approach equipped with a Goals Relational Graph (GRG) for tackling the partially observable goal-driven task, such as goal-driven visual navigation.

Hierarchical Reinforcement Learning Reinforcement Learning (RL) +1

Efficient Robotic Object Search via HIEM: Hierarchical Policy Learning with Intrinsic-Extrinsic Modeling

no code implementations16 Oct 2020 Xin Ye, Yezhou Yang

Despite the significant success at enabling robots with autonomous behaviors makes deep reinforcement learning a promising approach for robotic object search task, the deep reinforcement learning approach severely suffers from the nature sparse reward setting of the task.

Deep Reinforcement Learning Efficient Exploration +3

From Seeing to Moving: A Survey on Learning for Visual Indoor Navigation (VIN)

no code implementations26 Feb 2020 Xin Ye, Yezhou Yang

Visual Indoor Navigation (VIN) task has drawn increasing attention from the data-driven machine learning communities especially with the recently reported success from learning-based methods.

BIG-bench Machine Learning Visual Navigation

ROS-HPL: Robotic Object Search with Hierarchical Policy Learning and Intrinsic-Extrinsic Modeling

no code implementations25 Sep 2019 Xin Ye, Shibin Zheng, Yezhou Yang

Despite significant progress in Robotic Object Search (ROS) over the recent years with deep reinforcement learning based approaches, the sparsity issue in reward setting as well as the lack of interpretability of the previous ROS approaches leave much to be desired.

Deep Reinforcement Learning Object

Incremental Classifier Learning Based on PEDCC-Loss and Cosine Distance

no code implementations11 Jun 2019 Qiuyu Zhu, Zikuang He, Xin Ye

In this paper, we introduce an ensemble method of incremental classifier to alleviate this problem, which is based on the cosine distance between the output feature and the pre-defined center, and can let each task to be preserved in different networks.

Incremental Learning Knowledge Distillation

A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids

1 code implementation12 Apr 2019 Qiuyu Zhu, Pengju Zhang, Xin Ye

With the development of convolutional neural networks (CNNs) in recent years, the network structure has become more and more complex and varied, and has achieved very good results in pattern recognition, image classification, object detection and tracking.

Classification Face Recognition +4

GAPLE: Generalizable Approaching Policy LEarning for Robotic Object Searching in Indoor Environment

no code implementations21 Sep 2018 Xin Ye, Zhe Lin, Joon-Young Lee, Jianming Zhang, Shibin Zheng, Yezhou Yang

We study the problem of learning a generalizable action policy for an intelligent agent to actively approach an object of interest in an indoor environment solely from its visual inputs.

Semantic Segmentation Visual Navigation

Active Object Perceiver: Recognition-guided Policy Learning for Object Searching on Mobile Robots

no code implementations30 Jul 2018 Xin Ye, Zhe Lin, Haoxiang Li, Shibin Zheng, Yezhou Yang

We study the problem of learning a navigation policy for a robot to actively search for an object of interest in an indoor environment solely from its visual inputs.

Deep Reinforcement Learning Object +2

Crowd Counting Considering Network Flow Constraints in Videos

no code implementations12 May 2016 Liqing Gao, Yanzhang Wang, Xin Ye, Jian Wang

This paper, for the first time, introduces a quadratic programming model with the network flow constraints to improve the accuracy of crowd counting.

Crowd Counting regression

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