no code implementations • 28 Apr 2024 • Xiaolong Li, Jiawei Mo, Ying Wang, Chethan Parameshwara, Xiaohan Fei, Ashwin Swaminathan, Cj Taylor, Zhuowen Tu, Paolo Favaro, Stefano Soatto
In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achieving high fidelity by using a pre-trained multi-view diffusion model.
no code implementations • 16 Mar 2024 • Ziqi Lu, Jianbo Ye, Xiaohan Fei, Xiaolong Li, Jiawei Mo, Ashwin Swaminathan, Stefano Soatto
Neural Radiance Field (NeRF), as an implicit 3D scene representation, lacks inherent ability to accommodate changes made to the initial static scene.
no code implementations • 29 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.
no code implementations • 16 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.
no code implementations • 9 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.
no code implementations • 18 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.
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.
no code implementations • 6 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.
no code implementations • 18 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.
Ranked #17 on 3D Semantic Segmentation on SemanticKITTI
no code implementations • 24 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.
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.
no code implementations • 20 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.
no code implementations • 12 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.
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.
no code implementations • 1 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
no code implementations • COLING 2020 • Xiang Hu, Zujie Wen, Yafang Wang, Xiaolong Li, Gerard de Melo
In this work, we propose a reinforcement model to clarify ambiguous questions by suggesting refinements of the original query.
no code implementations • 14 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.
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.
no code implementations • ACL 2020 • Yangming Li, Kaisheng Yao, Libo Qin, Wanxiang Che, Xiaolong Li, Ting Liu
Data-driven approaches using neural networks have achieved promising performances in natural language generation (NLG).
no code implementations • 3 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.
no code implementations • 1 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.
no code implementations • 12 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.
no code implementations • 12 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.
no code implementations • 10 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.
no code implementations • 2 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.
no code implementations • 27 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.
no code implementations • 27 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).
1 code implementation • 27 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.
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.
no code implementations • 26 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.
no code implementations • WS 2019 • Xinze Guo, Chang Liu, Xiaolong Li, Yiran Wang, Guoliang Li, Feng Wang, Zhitao Xu, Liuyi Yang, Li Ma, Changliang Li
This paper describes the Kingsoft AI Lab{'}s submission to the WMT2019 news translation shared task.
no code implementations • 18 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.
no code implementations • 29 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.
no code implementations • NAACL 2018 • Cen Chen, Yinfei Yang, Jun Zhou, Xiaolong Li, Forrest Sheng Bao
With the growing amount of reviews in e-commerce websites, it is critical to assess the helpfulness of reviews and recommend them accordingly to consumers.
no code implementations • 11 May 2018 • Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Zhi-Hua Zhou, YUAN, QI
This model can block fraud transactions in a large amount of money each day.
no code implementations • 17 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.
no code implementations • 17 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.
no code implementations • 13 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.
no code implementations • 27 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.
no code implementations • 20 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.
3 code implementations • 3 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.
no code implementations • 2 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
no code implementations • 12 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.