Search Results for author: Xiaolong Li

Found 43 papers, 4 papers with code

A Quantitative Evaluation of Score Distillation Sampling Based Text-to-3D

no code implementations29 Feb 2024 Xiaohan Fei, Chethan Parameshwara, Jiawei Mo, Xiaolong Li, Ashwin Swaminathan, Cj Taylor, Paolo Favaro, Stefano Soatto

However, the SDS method is also the source of several artifacts, such as the Janus problem, the misalignment between the text prompt and the generated 3D model, and 3D model inaccuracies.

Image Generation Text to 3D

Anchor function: a type of benchmark functions for studying language models

no code implementations16 Jan 2024 Zhongwang Zhang, Zhiwei Wang, Junjie Yao, Zhangchen Zhou, Xiaolong Li, Weinan E, Zhi-Qin John Xu

However, language model research faces significant challenges, especially for academic research groups with constrained resources.

Language Modelling

BD-MSA: Body decouple VHR Remote Sensing Image Change Detection method guided by multi-scale feature information aggregation

no code implementations9 Jan 2024 Yonghui Tan, Xiaolong Li, Yishu Chen, Jinquan Ai

The purpose of remote sensing image change detection (RSCD) is to detect differences between bi-temporal images taken at the same place.

Change Detection

IntentDial: An Intent Graph based Multi-Turn Dialogue System with Reasoning Path Visualization

no code implementations18 Oct 2023 Zengguang Hao, Jie Zhang, Binxia Xu, Yafang Wang, Gerard de Melo, Xiaolong Li

Intent detection and identification from multi-turn dialogue has become a widely explored technique in conversational agents, for example, voice assistants and intelligent customer services.

Intent Detection

Group Pose: A Simple Baseline for End-to-End Multi-person Pose Estimation

2 code implementations ICCV 2023 Huan Liu, Qiang Chen, Zichang Tan, Jiang-Jiang Liu, Jian Wang, Xiangbo Su, Xiaolong Li, Kun Yao, Junyu Han, Errui Ding, Yao Zhao, Jingdong Wang

State-of-the-art solutions adopt the DETR-like framework, and mainly develop the complex decoder, e. g., regarding pose estimation as keypoint box detection and combining with human detection in ED-Pose, hierarchically predicting with pose decoder and joint (keypoint) decoder in PETR.

Human Detection Multi-Person Pose Estimation

Towards Visual Foundational Models of Physical Scenes

no code implementations6 Jun 2023 Chethan Parameshwara, Alessandro Achille, Xiaolong Li, Jiawei Mo, Matthew Trager, Ashwin Swaminathan, Cj Taylor, Dheera Venkatraman, Xiaohan Fei, Stefano Soatto

We describe a first step towards learning general-purpose visual representations of physical scenes using only image prediction as a training criterion.

Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation

no code implementations18 Oct 2022 Yangheng Zhao, Jun Wang, Xiaolong Li, Yue Hu, Ce Zhang, Yanfeng Wang, Siheng Chen

Instead of learning a single prototype for each class, in this paper, we propose to use an adaptive number of prototypes to dynamically describe the different point patterns within a semantic class.

3D Semantic Segmentation Scene Understanding +1

Tracking and Reconstructing Hand Object Interactions from Point Cloud Sequences in the Wild

no code implementations24 Sep 2022 Jiayi Chen, Mi Yan, Jiazhao Zhang, Yinzhen Xu, Xiaolong Li, Yijia Weng, Li Yi, Shuran Song, He Wang

We for the first time propose a point cloud based hand joint tracking network, HandTrackNet, to estimate the inter-frame hand joint motion.

hand-object pose Object +2

Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation

no code implementations NeurIPS 2021 Xiaolong Li, Yijia Weng, Li Yi, Leonidas Guibas, A. Lynn Abbott, Shuran Song, He Wang

Category-level object pose estimation aims to find 6D object poses of previously unseen object instances from known categories without access to object CAD models.

Object Pose Estimation +1

R4: A Framework for Route Representation and Route Recommendation

no code implementations20 Oct 2021 Ran Cheng, Chao Chen, Longfei Xu, Shen Li, Lei Wang, Hengbin Cui, Kaikui Liu, Xiaolong Li

For user representation, we utilize a series of historical navigation to extract user preference.


Denoising User-aware Memory Network for Recommendation

no code implementations12 Jul 2021 Zhi Bian, Shaojun Zhou, Hao Fu, Qihong Yang, Zhenqi Sun, Junjie Tang, Guiquan Liu, Kaikui Liu, Xiaolong Li

Specifically, the framework: (i) proposes a feature purification module based on orthogonal mapping, which use the representation of explicit feedback to purify the representation of implicit feedback, and effectively denoise the implicit feedback; (ii) designs a user memory network to model the long-term interests in a fine-grained way by improving the memory network, which is ignored by the existing methods; and (iii) develops a preference-aware interactive representation component to fuse the long-term and short-term interests of users based on gating to understand the evolution of unbiased preferences of users.


Leveraging SE(3) Equivariance for Self-supervised Category-Level Object Pose Estimation from Point Clouds

no code implementations NeurIPS 2021 Xiaolong Li, Yijia Weng, Li Yi, Leonidas Guibas, A. Lynn Abbott, Shuran Song, He Wang

To reduce the huge amount of pose annotations needed for category-level learning, we propose for the first time a self-supervised learning framework to estimate category-level 6D object pose from single 3D point clouds.

Object Pose Estimation +1

Super exponential divergence of periodic points for C^1-generic partially hyperbolic homoclinic classes

no code implementations1 Feb 2021 Xiaolong Li, Katsutoshi Shinohara

A diffeomorphism f is called super exponential divergent if for every r>1, the lower limit of #Per_n(f)/r^n diverges to infinity as n tends to infinity, where Per_n(f) is the set of all periodic points of f with period n. This property is stronger than the usual super exponential growth of the number of periodic points.

Dynamical Systems 37C20, 37C25, 37C29, 37D30

LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding

no code implementations14 Dec 2020 Hao Fu, Shaojun Zhou, Qihong Yang, Junjie Tang, Guiquan Liu, Kaikui Liu, Xiaolong Li

In this work, we propose a knowledge distillation method LRC-BERT based on contrastive learning to fit the output of the intermediate layer from the angular distance aspect, which is not considered by the existing distillation methods.

Contrastive Learning Knowledge Distillation +1

Handling Rare Entities for Neural Sequence Labeling

no code implementations ACL 2020 Yangming Li, Han Li, Kaisheng Yao, Xiaolong Li

One great challenge in neural sequence labeling is the data sparsity problem for rare entity words and phrases.

Unpack Local Model Interpretation for GBDT

no code implementations3 Apr 2020 Wenjing Fang, Jun Zhou, Xiaolong Li, Kenny Q. Zhu

Besides the commonly used feature importance as a global interpretation, feature contribution is a local measure that reveals the relationship between a specific instance and the related output.

Feature Importance

NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay

no code implementations1 Apr 2020 Jianbin Lin, Zhiqiang Zhang, Jun Zhou, Xiaolong Li, Jingli Fang, Yanming Fang, Quan Yu, Yuan Qi

Considering the above challenges and the special scenario in Ant Financial, we try to incorporate default prediction with network information to alleviate the cold-start problem.

Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization

no code implementations12 Mar 2020 Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li

However, existing MF approaches suffer from two major problems: (1) Expensive computations and storages due to the centralized model training mechanism: the centralized learners have to maintain the whole user-item rating matrix, and potentially huge low rank matrices.

Privacy Preserving

Local Contextual Attention with Hierarchical Structure for Dialogue Act Recognition

no code implementations12 Mar 2020 Zhigang Dai, Jinhua Fu, Qile Zhu, Hengbin Cui, Xiaolong Li, Yuan Qi

We revise the attention distribution to focus on the local and contextual semantic information by incorporating the relative position information between utterances.


RNE: A Scalable Network Embedding for Billion-scale Recommendation

no code implementations10 Mar 2020 Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan Qi

However, due to the huge number of users and items, the diversity and dynamic property of the user interest, how to design a scalable recommendation system, which is able to efficiently produce effective and diverse recommendation results on billion-scale scenarios, is still a challenging and open problem for existing methods.

Network Embedding

Long Short-Term Sample Distillation

no code implementations2 Mar 2020 Liang Jiang, Zujie Wen, Zhongping Liang, Yafang Wang, Gerard de Melo, Zhe Li, Liangzhuang Ma, Jiaxing Zhang, Xiaolong Li, Yuan Qi

The long-term teacher draws on snapshots from several epochs ago in order to provide steadfast guidance and to guarantee teacher--student differences, while the short-term one yields more up-to-date cues with the goal of enabling higher-quality updates.

Uncovering Insurance Fraud Conspiracy with Network Learning

no code implementations27 Feb 2020 Chen Liang, Ziqi Liu, Bin Liu, Jun Zhou, Xiaolong Li, Shuang Yang, Yuan Qi

In order to detect and prevent fraudulent insurance claims, we developed a novel data-driven procedure to identify groups of organized fraudsters, one of the major contributions to financial losses, by learning network information.

Fraud Detection Graph Learning

Heterogeneous Graph Neural Networks for Malicious Account Detection

1 code implementation27 Feb 2020 Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song

We present, GEM, the first heterogeneous graph neural network approach for detecting malicious accounts at Alipay, one of the world's leading mobile cashless payment platform.

How Much Can A Retailer Sell? Sales Forecasting on Tmall

no code implementations27 Feb 2020 Chaochao Chen, Ziqi Liu, Jun Zhou, Xiaolong Li, Yuan Qi, Yujing Jiao, Xingyu Zhong

By analyzing the data, we have two main observations, i. e., sales seasonality after we group different groups of retails and a Tweedie distribution after we transform the sales (target to forecast).

regression Time Series +1

Category-Level Articulated Object Pose Estimation

2 code implementations CVPR 2020 Xiaolong Li, He Wang, Li Yi, Leonidas Guibas, A. Lynn Abbott, Shuran Song

We develop a deep network based on PointNet++ that predicts ANCSH from a single depth point cloud, including part segmentation, normalized coordinates, and joint parameters in the canonical object space.

Object Pose Estimation

A Time Attention based Fraud Transaction Detection Framework

no code implementations26 Dec 2019 Longfei Li, Ziqi Liu, Chaochao Chen, Ya-Lin Zhang, Jun Zhou, Xiaolong Li

With online payment platforms being ubiquitous and important, fraud transaction detection has become the key for such platforms, to ensure user account safety and platform security.

TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial

no code implementations18 Jun 2019 Shaosheng Cao, Xinxing Yang, Cen Chen, Jun Zhou, Xiaolong Li, Yuan Qi

With the explosive growth of e-commerce and the booming of e-payment, detecting online transaction fraud in real time has become increasingly important to Fintech business.

Fraud Detection

Review Helpfulness Prediction with Embedding-Gated CNN

no code implementations29 Aug 2018 Cen Chen, Minghui Qiu, Yinfei Yang, Jun Zhou, Jun Huang, Xiaolong Li, Forrest Bao

Product reviews, in the form of texts dominantly, significantly help consumers finalize their purchasing decisions.


A Boosting Framework of Factorization Machine

no code implementations17 Apr 2018 Longfei Li, Peilin Zhao, Jun Zhou, Xiaolong Li

However, to choose the rank properly, it usually needs to run the algorithm for many times using different ranks, which clearly is inefficient for some large-scale datasets.

Recommendation Systems

Feature Propagation on Graph: A New Perspective to Graph Representation Learning

no code implementations17 Apr 2018 Biao Xiang, Ziqi Liu, Jun Zhou, Xiaolong Li

In this paper, we first define the concept of feature propagation on graph formally, and then study its convergence conditions to equilibrium states.

Graph Embedding Graph Representation Learning

Distributed Collaborative Hashing and Its Applications in Ant Financial

no code implementations13 Apr 2018 Chaochao Chen, Ziqi Liu, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li

The experimental results demonstrate that, comparing with the classic and state-of-the-art (distributed) latent factor models, DCH has comparable performance in terms of recommendation accuracy but has both fast convergence speed in offline model training procedure and realtime efficiency in online recommendation procedure.

Collaborative Filtering

Time-sensitive Customer Churn Prediction based on PU Learning

no code implementations27 Feb 2018 Li Wang, Chaochao Chen, Jun Zhou, Xiaolong Li

With the fast development of Internet companies throughout the world, customer churn has become a serious concern.

Non-Local Graph-Based Prediction For Reversible Data Hiding In Images

no code implementations20 Feb 2018 Qi Chang, Gene Cheung, Yao Zhao, Xiaolong Li, Rongrong Ni

If sufficiently smooth, we pose a maximum a posteriori (MAP) problem using either a quadratic Laplacian regularizer or a graph total variation (GTV) term as signal prior.

GeniePath: Graph Neural Networks with Adaptive Receptive Paths

3 code implementations3 Feb 2018 Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi

We present, GeniePath, a scalable approach for learning adaptive receptive fields of neural networks defined on permutation invariant graph data.

Secure Detection of Image Manipulation by means of Random Feature Selection

no code implementations2 Feb 2018 Zhipeng Chen, Benedetta Tondi, Xiaolong Li, Rongrong Ni, Yao Zhao, Mauro Barni

We address the problem of data-driven image manipulation detection in the presence of an attacker with limited knowledge about the detector.

Cryptography and Security

Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier

no code implementations12 Sep 2017 Zhiming Wang, Xiaolong Li, Jun Zhou

Mainly for the sake of solving the lack of keyword-specific data, we propose one Keyword Spotting (KWS) system using Deep Neural Network (DNN) and Connectionist Temporal Classifier (CTC) on power-constrained small-footprint mobile devices, taking full advantage of general corpus from continuous speech recognition which is of great amount.

Decision Making Small-Footprint Keyword Spotting +2

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