Search Results for author: Chang Liu

Found 314 papers, 111 papers with code

基于跨语言双语预训练及Bi-LSTM的汉-越平行句对抽取方法(Chinese-Vietnamese Parallel Sentence Pair Extraction Method Based on Cross-lingual Bilingual Pre-training and Bi-LSTM)

no code implementations CCL 2020 Chang Liu, Shengxiang Gao, Zhengtao Yu, Yuxin Huang, Congcong You

汉越平行句对抽取是缓解汉越平行语料库数据稀缺的重要方法。平行句对抽取可转换为同一语义空间下的句子相似性分类任务, 其核心在于双语语义空间对齐。传统语义空间对齐方法依赖于大规模的双语平行语料, 越南语作为低资源语言获取大规模平行语料相对困难。针对这个问题本文提出一种利用种子词典进行跨语言双语预训练及Bi-LSTM(Bi-directional Long Short-Term Memory)的汉-越平行句对抽取方法。预训练中仅需要大量的汉越单语和一个汉越种子词典, 通过利用汉越种子词典将汉越双语映射到公共语义空间进行词对齐。再利用Bi-LSTM和CNN(Convolutional Neural Networks)分别提取句子的全局特征和局部特征从而最大化表示汉-越句对之间的语义相关性。实验结果表明, 本文模型在F1得分上提升7. 1%, 优于基线模型。


面向人工智能伦理计算的中文道德词典构建方法研究(Construction of a Chinese Moral Dictionary for Artificial Intelligence Ethical Computing)

no code implementations CCL 2020 Hongrui Wang, Chang Liu, Dong Yu

道德词典资源的建设是人工智能伦理计算的一个研究重点。由于道德行为复杂多样, 现有的英文道德词典分类体系并不完善, 而中文方面目前尚未有相关的词典资源, 理论体系和构建方法仍待探究。针对以上问题, 该文提出了面向人工智能伦理计算的中文道德词典构建任务, 设计了四类标签和四种类型, 得到包含25, 012个词的中文道德词典资源。实验结果表明, 该词典资源不仅能够使机器学会道德知识, 判断词的道德标签和类型, 而且能够为句子级别的道德文本分析提供数据支持。

Reciprocal Learning of Knowledge Retriever and Response Ranker for Knowledge-Grounded Conversations

no code implementations COLING 2022 Jiazhan Feng, Chongyang Tao, Zhen Li, Chang Liu, Tao Shen, Dongyan Zhao

In this paper, we propose a reciprocal learning approach to jointly optimize a knowledge retriever and a response ranker for knowledge-grounded response retrieval without ground-truth knowledge labels.


Variance Reduction and Quasi-Newton for Particle-Based Variational Inference

no code implementations ICML 2020 Michael Zhu, Chang Liu, Jun Zhu

Particle-based Variational Inference methods (ParVIs), like Stein Variational Gradient Descent, are nonparametric variational inference methods that optimize a set of particles to best approximate a target distribution.

Bayesian Inference Riemannian optimization +1

ProphetChat: Enhancing Dialogue Generation with Simulation of Future Conversation

no code implementations ACL 2022 Chang Liu, Xu Tan, Chongyang Tao, Zhenxin Fu, Dongyan Zhao, Tie-Yan Liu, Rui Yan

To enable the chatbot to foresee the dialogue future, we design a beam-search-like roll-out strategy for dialogue future simulation using a typical dialogue generation model and a dialogue selector.

Dialogue Generation Response Generation

Make Your Actor Talk: Generalizable and High-Fidelity Lip Sync with Motion and Appearance Disentanglement

no code implementations12 Jun 2024 Runyi Yu, Tianyu He, Ailing Zhang, Yuchi Wang, Junliang Guo, Xu Tan, Chang Liu, Jie Chen, Jiang Bian

Instead, we propose to disentangle the motion and appearance, and then generate them one by one with a speech-to-motion diffusion model and a motion-conditioned appearance generation model.


Benchmarking Trustworthiness of Multimodal Large Language Models: A Comprehensive Study

no code implementations11 Jun 2024 Yichi Zhang, Yao Huang, Yitong Sun, Chang Liu, Zhe Zhao, Zhengwei Fang, Yifan Wang, Huanran Chen, Xiao Yang, Xingxing Wei, Hang Su, Yinpeng Dong, Jun Zhu

Despite the superior capabilities of Multimodal Large Language Models (MLLMs) across diverse tasks, they still face significant trustworthiness challenges.

Benchmarking Fairness

From Basic to Extra Features: Hypergraph Transformer Pretrain-then-Finetuning for Balanced Clinical Predictions on EHR

no code implementations9 Jun 2024 ran Xu, Yiwen Lu, Chang Liu, Yong Chen, Yan Sun, Xiao Hu, Joyce C Ho, Carl Yang

Electronic Health Records (EHRs) contain rich patient information and are crucial for clinical research and practice.

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models

no code implementations6 Jun 2024 Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei, Lin Huang, Lijun Wu, Bin Shao

In this study, we introduce a unified neural network architecture, the Deep Equilibrium Density Functional Theory Hamiltonian (DEQH) model, which incorporates Deep Equilibrium Models (DEQs) for predicting Density Functional Theory (DFT) Hamiltonians.

Convolutional Unscented Kalman Filter for Multi-Object Tracking with Outliers

no code implementations3 Jun 2024 Shiqi Liu, Wenhan Cao, Chang Liu, Tianyi Zhang, Shengbo Eben Li

Incorporating this operation into the widely used unscented Kalman filter (UKF) in commonly adopted tracking algorithms, we derive a variant of the UKF that is robust to outliers, called the convolutional UKF (ConvUKF).

Autonomous Driving Multi-Object Tracking

Networked Integrated Sensing and Communications for 6G Wireless Systems

no code implementations26 May 2024 Jiapeng Li, Xiaodan Shao, Feng Chen, Shaohua Wan, Chang Liu, Zhiqiang Wei, Derrick Wing Kwan Ng

Furthermore, we analyze the mean square error of the proposed distributed algorithm as a networked sensing performance metric and propose a beamforming design for the proposed network ISAC scheme to maximize the networked sensing accuracy and communication performance subject to a transmit power constraint.

Poisoning-based Backdoor Attacks for Arbitrary Target Label with Positive Triggers

no code implementations9 May 2024 Binxiao Huang, Jason Chun Lok, Chang Liu, Ngai Wong

To exploit the abundant information contained in the input data to output label mapping, our scheme utilizes the network trained from the clean dataset as a trigger generator to produce poisons that significantly raise the success rate of backdoor attacks versus conventional approaches.

Backdoor Attack

Assemblage: Automatic Binary Dataset Construction for Machine Learning

no code implementations7 May 2024 Chang Liu, Rebecca Saul, Yihao Sun, Edward Raff, Maya Fuchs, Townsend Southard Pantano, James Holt, Kristopher Micinski

Our results illustrate the practical need for robust corpuses of high-quality Windows PE binaries in training modern learning-based binary analyses.

Malware Classification

Intra-task Mutual Attention based Vision Transformer for Few-Shot Learning

no code implementations6 May 2024 Weihao Jiang, Chang Liu, Kun He

Specifically, we swap the class (CLS) token and patch tokens between the support and query sets to have the mutual attention, which enables each set to focus on the most useful information.

Few-Shot Learning

GraCo: Granularity-Controllable Interactive Segmentation

no code implementations CVPR 2024 Yian Zhao, Kehan Li, Zesen Cheng, Pengchong Qiao, Xiawu Zheng, Rongrong Ji, Chang Liu, Li Yuan, Jie Chen

In this work, we introduce Granularity-Controllable Interactive Segmentation (GraCo), a novel approach that allows precise control of prediction granularity by introducing additional parameters to input.

Interactive Segmentation Segmentation

UVMap-ID: A Controllable and Personalized UV Map Generative Model

1 code implementation22 Apr 2024 Weijie Wang, Jichao Zhang, Chang Liu, Xia Li, Xingqian Xu, Humphrey Shi, Nicu Sebe, Bruno Lepri

To solve the above problems, we introduce a novel method, UVMap-ID, which is a controllable and personalized UV Map generative model.


Large Language Models for Networking: Workflow, Advances and Challenges

no code implementations19 Apr 2024 Chang Liu, Xiaohui Xie, Xinggong Zhang, Yong Cui

The networking field is characterized by its high complexity and rapid iteration, requiring extensive expertise to accomplish network tasks, ranging from network design, configuration, diagnosis and security.

Feature Engineering Natural Language Understanding

Consisaug: A Consistency-based Augmentation for Polyp Detection in Endoscopy Image Analysis

1 code implementation17 Apr 2024 Ziyu Zhou, Wenyuan Shen, Chang Liu

Colorectal cancer (CRC), which frequently originates from initially benign polyps, remains a significant contributor to global cancer-related mortality.

Ray-driven Spectral CT Reconstruction Based on Neural Base-Material Fields

no code implementations10 Apr 2024 Ligen Shi, Chang Liu, Ping Yang, Jun Qiu, Xing Zhao

In spectral CT reconstruction, the basis materials decomposition involves solving a large-scale nonlinear system of integral equations, which is highly ill-posed mathematically.

Convolutional Bayesian Filtering

no code implementations30 Mar 2024 Wenhan Cao, Shiqi Liu, Chang Liu, Zeyu He, Stephen S. -T. Yau, Shengbo Eben Li

In this paper, we find that by adding an additional event that stipulates an inequality condition, we can transform the conditional probability into a special integration that is analogous to convolution.

ParCo: Part-Coordinating Text-to-Motion Synthesis

1 code implementation27 Mar 2024 Qiran Zou, Shangyuan Yuan, Shian Du, Yu Wang, Chang Liu, Yi Xu, Jie Chen, Xiangyang Ji

However, these methods encounter challenges such as the lack of coordination between different part motions and difficulties for networks to understand part concepts.

Motion Synthesis

Ultrafast Adaptive Primary Frequency Tuning and Secondary Frequency Identification for S/S WPT system

no code implementations26 Mar 2024 Chang Liu, Wei Han, Guangyu Yan, Bowang Zhang, Chunlin Li

The swift response of SCC and two-step perturb-and-observe algorithm mitigate output disturbances, thereby expediting the frequency tuning process.

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction

no code implementations14 Mar 2024 He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu

Predicting the mean-field Hamiltonian matrix in density functional theory is a fundamental formulation to leverage machine learning for solving molecular science problems.

Property Prediction

AnatoMix: Anatomy-aware Data Augmentation for Multi-organ Segmentation

no code implementations5 Mar 2024 Chang Liu, Fuxin Fan, Annette Schwarz, Andreas Maier

Multi-organ segmentation in medical images is a widely researched task and can save much manual efforts of clinicians in daily routines.

Anatomy Data Augmentation +2

DOZE: A Dataset for Open-Vocabulary Zero-Shot Object Navigation in Dynamic Environments

no code implementations29 Feb 2024 Ji Ma, Hongming Dai, Yao Mu, Pengying Wu, Hao Wang, Xiaowei Chi, Yang Fei, Shanghang Zhang, Chang Liu

Zero-Shot Object Navigation (ZSON) requires agents to autonomously locate and approach unseen objects in unfamiliar environments and has emerged as a particularly challenging task within the domain of Embodied AI.

Attribute Collision Avoidance +2

Path Planning based on 2D Object Bounding-box

no code implementations22 Feb 2024 Yanliang Huang, Liguo Zhou, Chang Liu, Alois Knoll

The implementation of Autonomous Driving (AD) technologies within urban environments presents significant challenges.

Autonomous Driving Graph Neural Network +3

Two-View Topogram-Based Anatomy-Guided CT Reconstruction for Prospective Risk Minimization

no code implementations23 Jan 2024 Chang Liu, Laura Klein, Yixing Huang, Edith Baader, Michael Lell, Marc Kachelrieß, Andreas Maier

The average organ dice of the proposed method is 0. 71 compared with 0. 63 in baseline model, indicating the enhancement of anatomical structures.

Anatomy Generative Adversarial Network +3

Error bounds of constant gain least-mean-squares algorithms

no code implementations20 Jan 2024 Chang Liu, Antwan D. Clark

Constant gain least-mean-squares (LMS) algorithms have a wide range of applications in trajectory tracking problems, but the formal convergence of LMS in mean square is not yet fully established.

Instance Brownian Bridge as Texts for Open-vocabulary Video Instance Segmentation

1 code implementation18 Jan 2024 Zesen Cheng, Kehan Li, Hao Li, Peng Jin, Chang Liu, Xiawu Zheng, Rongrong Ji, Jie Chen

To mold instance queries to follow Brownian bridge and accomplish alignment with class texts, we design Bridge-Text Alignment (BTA) to learn discriminative bridge-level representations of instances via contrastive objectives.

Instance Segmentation Semantic Segmentation +1

VoroNav: Voronoi-based Zero-shot Object Navigation with Large Language Model

no code implementations5 Jan 2024 Pengying Wu, Yao Mu, Bingxian Wu, Yi Hou, Ji Ma, Shanghang Zhang, Chang Liu

In the realm of household robotics, the Zero-Shot Object Navigation (ZSON) task empowers agents to adeptly traverse unfamiliar environments and locate objects from novel categories without prior explicit training.

Language Modelling Large Language Model

Intelligent Grimm - Open-ended Visual Storytelling via Latent Diffusion Models

no code implementations CVPR 2024 Chang Liu, HaoNing Wu, Yujie Zhong, Xiaoyun Zhang, Yanfeng Wang, Weidi Xie

Generative models have recently exhibited exceptional capabilities in text-to-image generation but still struggle to generate image sequences coherently.

Text-to-Image Generation Visual Storytelling

Learning Spatially Collaged Fourier Bases for Implicit Neural Representation

no code implementations28 Dec 2023 Jason Chun Lok Li, Chang Liu, Binxiao Huang, Ngai Wong

Existing approaches to Implicit Neural Representation (INR) can be interpreted as a global scene representation via a linear combination of Fourier bases of different frequencies.

3D Reconstruction 3D Shape Representation

Future-proofing geotechnics workflows: accelerating problem-solving with large language models

no code implementations14 Dec 2023 Stephen Wu, Yu Otake, Daijiro Mizutani, Chang Liu, Kotaro Asano, Nana Sato, Hidetoshi Baba, Yusuke Fukunaga, Yosuke Higo, Akiyoshi Kamura, Shinnosuke Kodama, Masataka Metoki, Tomoka Nakamura, Yuto Nakazato, Taiga Saito, Akihiro Shioi, Masahiro Takenobu, Keigo Tsukioka, Ryo Yoshikawa

The integration of Large Language Models (LLMs) like ChatGPT into the workflows of geotechnical engineering has a high potential to transform how the discipline approaches problem-solving and decision-making.

Decision Making

Offloading and Quality Control for AI Generated Content Services in 6G Mobile Edge Computing Networks

no code implementations11 Dec 2023 Yitong Wang, Chang Liu, Jun Zhao

In pursuit of enhancing the accessibility of AIGC services, the deployment of AIGC models (e. g., diffusion models) to edge servers and local devices has become a prevailing trend.


iDesigner: A High-Resolution and Complex-Prompt Following Text-to-Image Diffusion Model for Interior Design

no code implementations7 Dec 2023 Ruyi Gan, XiaoJun Wu, Junyu Lu, Yuanhe Tian, Dixiang Zhang, Ziwei Wu, Renliang Sun, Chang Liu, Jiaxing Zhang, Pingjian Zhang, Yan Song

However, there are few specialized models in certain domains, such as interior design, which is attributed to the complex textual descriptions and detailed visual elements inherent in design, alongside the necessity for adaptable resolution.

Image Generation

Optimal Wildfire Escape Route Planning for Drones under Dynamic Fire and Smoke

no code implementations6 Dec 2023 Chang Liu, Tamas Sziranyi

This work focuses on the development of an optimal wildfire escape route planning system specifically designed for drones, considering dynamic fire and smoke models.

Active Wildfires Detection and Dynamic Escape Routes Planning for Humans through Information Fusion between Drones and Satellites

no code implementations6 Dec 2023 Chang Liu, Tamas Sziranyi

Taking the Chongqing wildfire on August 24, 2022, as a case study, the results demonstrate that the dynamic escape route planning algorithm can provide an optimal real-time navigation path for humans in the presence of fire through the information fusion of UAVs and satellites.

Road Segmentation

Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning

2 code implementations5 Dec 2023 Zhuo Huang, Chang Liu, Yinpeng Dong, Hang Su, Shibao Zheng, Tongliang Liu

Concretely, by estimating a transition matrix that captures the probability of one class being confused with another, an instruction containing a correct exemplar and an erroneous one from the most probable noisy class can be constructed.

Denoising In-Context Learning

FreestyleRet: Retrieving Images from Style-Diversified Queries

1 code implementation5 Dec 2023 Hao Li, Curise Jia, Peng Jin, Zesen Cheng, Kehan Li, Jialu Sui, Chang Liu, Li Yuan

In this paper, we propose the Style-Diversified Query-Based Image Retrieval task, which enables retrieval based on various query styles.

Image Retrieval Retrieval

LLMs Accelerate Annotation for Medical Information Extraction

no code implementations4 Dec 2023 Akshay Goel, Almog Gueta, Omry Gilon, Chang Liu, Sofia Erell, Lan Huong Nguyen, Xiaohong Hao, Bolous Jaber, Shashir Reddy, Rupesh Kartha, Jean Steiner, Itay Laish, Amir Feder

The results highlight the potential of using LLMs to improve the utilization of unstructured clinical data, allowing for the swift deployment of tailored NLP solutions in healthcare.

text annotation

Transformer-empowered Multi-modal Item Embedding for Enhanced Image Search in E-Commerce

no code implementations29 Nov 2023 Chang Liu, Peng Hou, AnXiang Zeng, Han Yu

Since its deployment in March 2023, it has achieved a remarkable 9. 90% increase in terms of clicks per user and a 4. 23% boost in terms of orders per user for the image search feature on the Shopee e-commerce platform.

Image Retrieval Retrieval

Street TryOn: Learning In-the-Wild Virtual Try-On from Unpaired Person Images

1 code implementation27 Nov 2023 Aiyu Cui, Jay Mahajan, Viraj Shah, Preeti Gomathinayagam, Chang Liu, Svetlana Lazebnik

By contrast, it is hard to collect paired data for in-the-wild scenes, and therefore, virtual try-on for casual images of people with more diverse poses against cluttered backgrounds is rarely studied.

Image Generation Semantic Segmentation +4

A Systematic Review of Deep Learning-based Research on Radiology Report Generation

1 code implementation23 Nov 2023 Chang Liu, Yuanhe Tian, Yan Song

Specifically, we firstly cover pivotal RRG approaches based on the task-specific features of radiographs, reports, and the cross-modal relations between them, and then illustrate the benchmark datasets conventionally used for this task with evaluation metrics, subsequently analyze the performance of different approaches and finally offer our summary on the challenges and the trends in future directions.

GMTR: Graph Matching Transformers

1 code implementation14 Nov 2023 Jinpei Guo, Shaofeng Zhang, Runzhong Wang, Chang Liu, Junchi Yan

Meanwhile, on Pascal VOC, QueryTrans improves the accuracy of NGMv2 from $80. 1\%$ to $\mathbf{83. 3\%}$, and BBGM from $79. 0\%$ to $\mathbf{84. 5\%}$.

 Ranked #1 on Graph Matching on PASCAL VOC (matching accuracy metric)

Graph Attention Graph Matching +2

YOLO-BEV: Generating Bird's-Eye View in the Same Way as 2D Object Detection

no code implementations26 Oct 2023 Chang Liu, Liguo Zhou, Yanliang Huang, Alois Knoll

Vehicle perception systems strive to achieve comprehensive and rapid visual interpretation of their surroundings for improved safety and navigation.

Autonomous Driving object-detection +1

Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning

no code implementations28 Sep 2023 He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao

Orbital-free density functional theory (OFDFT) is a quantum chemistry formulation that has a lower cost scaling than the prevailing Kohn-Sham DFT, which is increasingly desired for contemporary molecular research.

RECALL+: Adversarial Web-based Replay for Continual Learning in Semantic Segmentation

no code implementations19 Sep 2023 Chang Liu, Giulia Rizzoli, Francesco Barbato, Andrea Maracani, Marco Toldo, Umberto Michieli, Yi Niu, Pietro Zanuttigh

Catastrophic forgetting of previous knowledge is a critical issue in continual learning typically handled through various regularization strategies.

Continual Learning Incremental Learning +1

Retinex-guided Channel-grouping based Patch Swap for Arbitrary Style Transfer

no code implementations19 Sep 2023 Chang Liu, Yi Niu, Mingming Ma, Fu Li, Guangming Shi

The basic principle of the patch-matching based style transfer is to substitute the patches of the content image feature maps by the closest patches from the style image feature maps.

Patch Matching Style Transfer

UNIDEAL: Curriculum Knowledge Distillation Federated Learning

no code implementations16 Sep 2023 Yuwen Yang, Chang Liu, Xun Cai, Suizhi Huang, Hongtao Lu, Yue Ding

Federated Learning (FL) has emerged as a promising approach to enable collaborative learning among multiple clients while preserving data privacy.

Federated Learning Knowledge Distillation

Towards Real-World Burst Image Super-Resolution: Benchmark and Method

1 code implementation ICCV 2023 Pengxu Wei, Yujing Sun, Xingbei Guo, Chang Liu, Jie Chen, Xiangyang Ji, Liang Lin

Despite substantial advances, single-image super-resolution (SISR) is always in a dilemma to reconstruct high-quality images with limited information from one input image, especially in realistic scenarios.

Burst Image Super-Resolution

GREC: Generalized Referring Expression Comprehension

1 code implementation30 Aug 2023 Shuting He, Henghui Ding, Chang Liu, Xudong Jiang

This dataset encompasses a range of expressions: those referring to multiple targets, expressions with no specific target, and the single-target expressions.

Generalized Referring Expression Comprehension Referring Expression +1

Evaluating Large Language Models on Graphs: Performance Insights and Comparative Analysis

1 code implementation22 Aug 2023 Chang Liu, Bo Wu

Yet, the application of LLMs to graph data remains under-explored.

MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions

1 code implementation ICCV 2023 Henghui Ding, Chang Liu, Shuting He, Xudong Jiang, Chen Change Loy

To investigate the feasibility of using motion expressions to ground and segment objects in videos, we propose a large-scale dataset called MeViS, which contains numerous motion expressions to indicate target objects in complex environments.

Motion Expressions Guided Video Segmentation Object +6

Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation

1 code implementation14 Jul 2023 Jingna Qiu, Frauke Wilm, Mathias Öttl, Maja Schlereth, Chang Liu, Tobias Heimann, Marc Aubreville, Katharina Breininger

We find that the efficiency of this method highly depends on the choice of AL step size (i. e., the combination of region size and the number of selected regions per WSI), and a suboptimal AL step size can result in redundant annotation requests or inflated computation costs.

Active Learning Informativeness +2

GujiBERT and GujiGPT: Construction of Intelligent Information Processing Foundation Language Models for Ancient Texts

no code implementations11 Jul 2023 Dongbo Wang, Chang Liu, Zhixiao Zhao, Si Shen, Liu Liu, Bin Li, Haotian Hu, Mengcheng Wu, Litao Lin, Xue Zhao, Xiyu Wang

In the context of the rapid development of large language models, we have meticulously trained and introduced the GujiBERT and GujiGPT language models, which are foundational models specifically designed for intelligent information processing of ancient texts.

Model Selection Part-Of-Speech Tagging +2

Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train

1 code implementation29 Jun 2023 Zhao Wang, Chang Liu, Shaoting Zhang, Qi Dou

Foundation models have exhibited remarkable success in various applications, such as disease diagnosis and text report generation.

Segmentation Transfer Learning

Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning

no code implementations8 Jun 2023 Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu

In this paper, we introduce a novel deep learning framework, called Distributional Graphormer (DiG), in an attempt to predict the equilibrium distribution of molecular systems.

Intelligent Grimm -- Open-ended Visual Storytelling via Latent Diffusion Models

1 code implementation1 Jun 2023 Chang Liu, HaoNing Wu, Yujie Zhong, Xiaoyun Zhang, Yanfeng Wang, Weidi Xie

Generative models have recently exhibited exceptional capabilities in text-to-image generation, but still struggle to generate image sequences coherently.

Story Visualization Style Transfer +2

Towards Interactive Image Inpainting via Sketch Refinement

1 code implementation1 Jun 2023 Chang Liu, Shunxin Xu, Jialun Peng, Kaidong Zhang, Dong Liu

To address this problem, we propose a two-stage image inpainting method termed SketchRefiner.

Image Inpainting

Fast Matrix Multiplication Without Tears: A Constraint Programming Approach

1 code implementation1 Jun 2023 Arnaud Deza, Chang Liu, Pashootan Vaezipoor, Elias B. Khalil

In this work, we propose a simple yet novel Constraint Programming approach to find non-commutative algorithms for fast matrix multiplication or provide proof of infeasibility otherwise.

Problem Decomposition valid

Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning

1 code implementation CVPR 2023 Yu Wang, Pengchong Qiao, Chang Liu, Guoli Song, Xiawu Zheng, Jie Chen

We argue that an overlooked problem of robust SSL is its corrupted information on semantic level, practically limiting the development of the field.

More than Classification: A Unified Framework for Event Temporal Relation Extraction

no code implementations28 May 2023 Quzhe Huang, Yutong Hu, Shengqi Zhu, Yansong Feng, Chang Liu, Dongyan Zhao

After examining the relation definitions in various ETRE tasks, we observe that all relations can be interpreted using the start and end time points of events.

Multi-Label Classification Relation +1

Multi-Modal Mutual Attention and Iterative Interaction for Referring Image Segmentation

no code implementations24 May 2023 Chang Liu, Henghui Ding, Yulun Zhang, Xudong Jiang

However, the generic attention mechanism in Transformer only uses the language input for attention weight calculation, which does not explicitly fuse language features in its output.

Decoder Image Segmentation +1

Tokenized Graph Transformer with Neighborhood Augmentation for Node Classification in Large Graphs

no code implementations22 May 2023 Jinsong Chen, Chang Liu, Kaiyuan Gao, Gaichao Li, Kun He

Graph Transformers, emerging as a new architecture for graph representation learning, suffer from the quadratic complexity on the number of nodes when handling large graphs.

Data Augmentation Graph Representation Learning +1

Text-Video Retrieval with Disentangled Conceptualization and Set-to-Set Alignment

4 code implementations20 May 2023 Peng Jin, Hao Li, Zesen Cheng, Jinfa Huang, Zhennan Wang, Li Yuan, Chang Liu, Jie Chen

In this paper, we propose the Disentangled Conceptualization and Set-to-set Alignment (DiCoSA) to simulate the conceptualizing and reasoning process of human beings.

Retrieval Video Retrieval

LaCon: Late-Constraint Diffusion for Steerable Guided Image Synthesis

1 code implementation19 May 2023 Chang Liu, Rui Li, Kaidong Zhang, Xin Luo, Dong Liu

To offer more controllability for the generation process, existing studies, termed as early-constraint methods in this paper, leverage extra conditions and incorporate them into pre-trained diffusion models.

Conditional Image Generation Conditional Text-to-Image Synthesis

Scribble-Supervised Target Extraction Method Based on Inner Structure-Constraint for Remote Sensing Images

1 code implementation18 May 2023 Yitong Li, Chang Liu, Jie Ma

Weakly supervised learning based on scribble annotations in target extraction of remote sensing images has drawn much interest due to scribbles' flexibility in denoting winding objects and low cost of manually labeling.

Decoder Weakly-supervised Learning

TG-VQA: Ternary Game of Video Question Answering

no code implementations17 May 2023 Hao Li, Peng Jin, Zesen Cheng, Songyang Zhang, Kai Chen, Zhennan Wang, Chang Liu, Jie Chen

Video question answering aims at answering a question about the video content by reasoning the alignment semantics within them.

Contrastive Learning Question Answering +2

Watermarking Text Generated by Black-Box Language Models

1 code implementation14 May 2023 Xi Yang, Kejiang Chen, Weiming Zhang, Chang Liu, Yuang Qi, Jie Zhang, Han Fang, Nenghai Yu

To allow third-parties to autonomously inject watermarks into generated text, we develop a watermarking framework for black-box language model usage scenarios.

Adversarial Robustness Language Modelling +2

Hail Mary Pass: Contests with Stochastic Progress

no code implementations12 May 2023 Chang Liu

This paper studies the equilibrium behavior in contests with stochastic progress.


Shotgun crystal structure prediction using machine-learned formation energies

1 code implementation3 May 2023 Chang Liu, Hiromasa Tamaki, Tomoyasu Yokoyama, Kensuke Wakasugi, Satoshi Yotsuhashi, Minoru Kusaba, Ryo Yoshida

Stable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface defined on the space of the atomic configurations.

Transfer Learning

Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition

1 code implementation CVPR 2023 Xiao Yang, Chang Liu, Longlong Xu, Yikai Wang, Yinpeng Dong, Ning Chen, Hang Su, Jun Zhu

The goal of this work is to develop a more reliable technique that can carry out an end-to-end evaluation of adversarial robustness for commercial systems.

Adversarial Robustness Face Recognition

Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection

1 code implementation CVPR 2023 Chang Liu, Weiming Zhang, Xiangru Lin, Wei zhang, Xiao Tan, Junyu Han, Xiaomao Li, Errui Ding, Jingdong Wang

It employs a "divide-and-conquer" strategy and separately exploits positives for the classification and localization task, which is more robust to the assignment ambiguity.

Dense Object Detection Object +3

Context-Aware Transformer for 3D Point Cloud Automatic Annotation

no code implementations27 Mar 2023 Xiaoyan Qian, Chang Liu, Xiaojuan Qi, Siew-Chong Tan, Edmund Lam, Ngai Wong

3D automatic annotation has received increased attention since manually annotating 3D point clouds is laborious.

Decoder Object

Frame Flexible Network

2 code implementations CVPR 2023 Yitian Zhang, Yue Bai, Chang Liu, Huan Wang, Sheng Li, Yun Fu

To fix this issue, we propose a general framework, named Frame Flexible Network (FFN), which not only enables the model to be evaluated at different frames to adjust its computation, but also reduces the memory costs of storing multiple models significantly.

Video Recognition

Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning

4 code implementations CVPR 2023 Peng Jin, Jinfa Huang, Pengfei Xiong, Shangxuan Tian, Chang Liu, Xiangyang Ji, Li Yuan, Jie Chen

Contrastive learning-based video-language representation learning approaches, e. g., CLIP, have achieved outstanding performance, which pursue semantic interaction upon pre-defined video-text pairs.

Contrastive Learning Question Answering +5

Multi-granularity Interaction Simulation for Unsupervised Interactive Segmentation

no code implementations ICCV 2023 Kehan Li, Yian Zhao, Zhennan Wang, Zesen Cheng, Peng Jin, Xiangyang Ji, Li Yuan, Chang Liu, Jie Chen

Interactive segmentation enables users to segment as needed by providing cues of objects, which introduces human-computer interaction for many fields, such as image editing and medical image analysis.

Interactive Segmentation

DiffusionRet: Generative Text-Video Retrieval with Diffusion Model

4 code implementations ICCV 2023 Peng Jin, Hao Li, Zesen Cheng, Kehan Li, Xiangyang Ji, Chang Liu, Li Yuan, Jie Chen

Existing text-video retrieval solutions are, in essence, discriminant models focused on maximizing the conditional likelihood, i. e., p(candidates|query).

Retrieval Video Retrieval

Parallel Vertex Diffusion for Unified Visual Grounding

no code implementations13 Mar 2023 Zesen Cheng, Kehan Li, Peng Jin, Xiangyang Ji, Li Yuan, Chang Liu, Jie Chen

An intuitive materialization of our paradigm is Parallel Vertex Diffusion (PVD) to directly set vertex coordinates as the generation target and use a diffusion model to train and infer.

Visual Grounding

Stock Price Prediction Using Temporal Graph Model with Value Chain Data

no code implementations7 Mar 2023 Chang Liu, Sandra Paterlini

Stock price prediction is a crucial element in financial trading as it allows traders to make informed decisions about buying, selling, and holding stocks.

Stock Price Prediction

Image as Set of Points

2 code implementations2 Mar 2023 Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu

Context clusters (CoCs) view an image as a set of unorganized points and extract features via simplified clustering algorithm.


Ultra-low Precision Multiplication-free Training for Deep Neural Networks

no code implementations28 Feb 2023 Chang Liu, Rui Zhang, Xishan Zhang, Yifan Hao, Zidong Du, Xing Hu, Ling Li, Qi Guo

The energy-efficient works try to decrease the precision of multiplication or replace the multiplication with energy-efficient operations such as addition or bitwise shift, to reduce the energy consumption of FP32 multiplications.


Particle-based Online Bayesian Sampling

no code implementations28 Feb 2023 Yifan Yang, Chang Liu, Zheng Zhang

Online optimization has gained increasing interest due to its capability of tracking real-world streaming data.

Variational Inference

A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking

no code implementations28 Feb 2023 Chang Liu, Yinpeng Dong, Wenzhao Xiang, Xiao Yang, Hang Su, Jun Zhu, Yuefeng Chen, Yuan He, Hui Xue, Shibao Zheng

In our benchmark, we evaluate the robustness of 55 typical deep learning models on ImageNet with diverse architectures (e. g., CNNs, Transformers) and learning algorithms (e. g., normal supervised training, pre-training, adversarial training) under numerous adversarial attacks and out-of-distribution (OOD) datasets.

Adversarial Robustness Benchmarking +2

Improving Model Generalization by On-manifold Adversarial Augmentation in the Frequency Domain

no code implementations28 Feb 2023 Chang Liu, Wenzhao Xiang, Yuan He, Hui Xue, Shibao Zheng, Hang Su

To address this issue, we proposed a novel method of Augmenting data with Adversarial examples via a Wavelet module (AdvWavAug), an on-manifold adversarial data augmentation technique that is simple to implement.

Data Augmentation

MOSE: A New Dataset for Video Object Segmentation in Complex Scenes

1 code implementation ICCV 2023 Henghui Ding, Chang Liu, Shuting He, Xudong Jiang, Philip H. S. Torr, Song Bai

However, since the target objects in these existing datasets are usually relatively salient, dominant, and isolated, VOS under complex scenes has rarely been studied.

Object Segmentation +3

UATVR: Uncertainty-Adaptive Text-Video Retrieval

1 code implementation ICCV 2023 Bo Fang, Wenhao Wu, Chang Liu, Yu Zhou, Yuxin Song, Weiping Wang, Xiangbo Shu, Xiangyang Ji, Jingdong Wang

In the refined embedding space, we represent text-video pairs as probabilistic distributions where prototypes are sampled for matching evaluation.

Retrieval Semantic correspondence +1

TopoSeg: Topology-Aware Nuclear Instance Segmentation

no code implementations ICCV 2023 Hongliang He, Jun Wang, Pengxu Wei, Fan Xu, Xiangyang Ji, Chang Liu, Jie Chen

Experiments on three nuclear instance segmentation datasets justify the superiority of TopoSeg, which achieves state-of-the-art performance.

Instance Segmentation Segmentation +1

Disjoint Masking with Joint Distillation for Efficient Masked Image Modeling

1 code implementation31 Dec 2022 Xin Ma, Chang Liu, Chunyu Xie, Long Ye, Yafeng Deng, Xiangyang Ji

Masked image modeling (MIM) has shown great promise for self-supervised learning (SSL) yet been criticized for learning inefficiency.

object-detection Object Detection +2

Predictive Precoder Design for OTFS-Enabled URLLC: A Deep Learning Approach

no code implementations28 Dec 2022 Chang Liu, Shuangyang Li, Weijie Yuan, Xuemeng Liu, Derrick Wing Kwan Ng

This paper investigates the orthogonal time frequency space (OTFS) transmission for enabling ultra-reliable low-latency communications (URLLC).

Adam: Dense Retrieval Distillation with Adaptive Dark Examples

no code implementations20 Dec 2022 Chongyang Tao, Chang Liu, Tao Shen, Can Xu, Xiubo Geng, Binxing Jiao, Daxin Jiang

Different from previous works that only rely on one positive and hard negatives as candidate passages, we create dark examples that all have moderate relevance to the query through mixing-up and masking in discrete space.

Knowledge Distillation Retrieval

DQnet: Cross-Model Detail Querying for Camouflaged Object Detection

no code implementations16 Dec 2022 Wei Sun, Chengao Liu, Linyan Zhang, Yu Li, Pengxu Wei, Chang Liu, Jialing Zou, Jianbin Jiao, Qixiang Ye

Optimizing a convolutional neural network (CNN) for camouflaged object detection (COD) tends to activate local discriminative regions while ignoring complete object extent, causing the partial activation issue which inevitably leads to missing or redundant regions of objects.

Object object-detection +2

Proposal Distribution Calibration for Few-Shot Object Detection

1 code implementation15 Dec 2022 Bohao Li, Chang Liu, Mengnan Shi, Xiaozhong Chen, Xiangyang Ji, Qixiang Ye

Adapting object detectors learned with sufficient supervision to novel classes under low data regimes is charming yet challenging.

Few-Shot Object Detection Object +1

THMA: Tencent HD Map AI System for Creating HD Map Annotations

no code implementations14 Dec 2022 Kun Tang, Xu Cao, Zhipeng Cao, Tong Zhou, Erlong Li, Ao Liu, Shengtao Zou, Chang Liu, Shuqi Mei, Elena Sizikova, Chao Zheng

THMA has been deployed by the Tencent Map team to provide services to downstream companies and users, serving over 1, 000 labeling workers and producing more than 30, 000 kilometers of HD map data per day at most.

Active Learning Weakly-supervised Learning

Robust Contracts with Exploration

no code implementations30 Nov 2022 Chang Liu

We study a two-period moral hazard problem; there are two agents, with action sets that are unknown to the principal.

ILSGAN: Independent Layer Synthesis for Unsupervised Foreground-Background Segmentation

1 code implementation25 Nov 2022 Qiran Zou, Yu Yang, Wing Yin Cheung, Chang Liu, Xiangyang Ji

Unsupervised foreground-background segmentation aims at extracting salient objects from cluttered backgrounds, where Generative Adversarial Network (GAN) approaches, especially layered GANs, show great promise.

Generative Adversarial Network Image Generation +4

Scalable Predictive Beamforming for IRS-Assisted Multi-User Communications: A Deep Learning Approach

no code implementations23 Nov 2022 Chang Liu, Xuemeng Liu, Zhiqiang Wei, Derrick Wing Kwan Ng, Robert Schober

With the proposed predictive approach, we can avoid full-scale CSI estimation and facilitate low-dimensional CE for transmit beamforming design such that the signaling overhead is reduced by a scale of $\frac{1}{N}$, where $N$ is the number of IRS elements.

Graph Neural Network

EDEN: A Plug-in Equivariant Distance Encoding to Beyond the 1-WL Test

no code implementations19 Nov 2022 Chang Liu, Yuwen Yang, Yue Ding, Hongtao Lu

While most existing message-passing graph neural networks (MPNNs) are permutation-invariant in graph-level representation learning and permutation-equivariant in node- and edge-level representation learning, their expressive power is commonly limited by the 1-Weisfeiler-Lehman (1-WL) graph isomorphism test.

Graph Representation Learning

Local Magnification for Data and Feature Augmentation

no code implementations15 Nov 2022 Kun He, Chang Liu, Stephen Lin, John E. Hopcroft

And further combination with our feature augmentation techniques, termed LOMA_IF&FO, can continue to strengthen the model and outperform advanced intensity transformation methods for data augmentation.

Data Augmentation Image Classification +2

Distilling Representations from GAN Generator via Squeeze and Span

1 code implementation6 Nov 2022 Yu Yang, Xiaotian Cheng, Chang Liu, Hakan Bilen, Xiangyang Ji

In recent years, generative adversarial networks (GANs) have been an actively studied topic and shown to successfully produce high-quality realistic images in various domains.

Representation Learning

Local Manifold Augmentation for Multiview Semantic Consistency

no code implementations5 Nov 2022 Yu Yang, Wing Yin Cheung, Chang Liu, Xiangyang Ji

Multiview self-supervised representation learning roots in exploring semantic consistency across data of complex intra-class variation.

Representation Learning Self-Supervised Learning

Beyond Instance Discrimination: Relation-aware Contrastive Self-supervised Learning

no code implementations2 Nov 2022 Yifei Zhang, Chang Liu, Yu Zhou, Weiping Wang, Qixiang Ye, Xiangyang Ji

In this paper, we present relation-aware contrastive self-supervised learning (ReCo) to integrate instance relations, i. e., global distribution relation and local interpolation relation, into the CSL framework in a plug-and-play fashion.

Relation Self-Supervised Learning

Position-Aware Subgraph Neural Networks with Data-Efficient Learning

1 code implementation1 Nov 2022 Chang Liu, Yuwen Yang, Zhe Xie, Hongtao Lu, Yue Ding

2) Prevailing graph augmentation methods for GEL, including rule-based, sample-based, adaptive, and automated methods, are not suitable for augmenting subgraphs because a subgraph contains fewer nodes but richer information such as position, neighbor, and structure.

Contrastive Learning Position +1

Completely Heterogeneous Federated Learning

no code implementations28 Oct 2022 Chang Liu, Yuwen Yang, Xun Cai, Yue Ding, Hongtao Lu

Federated learning (FL) faces three major difficulties: cross-domain, heterogeneous models, and non-i. i. d.

Data-free Knowledge Distillation Federated Learning

VLT: Vision-Language Transformer and Query Generation for Referring Segmentation

1 code implementation28 Oct 2022 Henghui Ding, Chang Liu, Suchen Wang, Xudong Jiang

We propose a Vision-Language Transformer (VLT) framework for referring segmentation to facilitate deep interactions among multi-modal information and enhance the holistic understanding to vision-language features.

Referring Expression Segmentation Referring Video Object Segmentation

Matching entropy based disparity estimation from light field

no code implementations28 Oct 2022 Ligen Shi, Chang Liu, Di He, Xing Zhao, Jun Qiu

A major challenge for matching-based depth estimation is to prevent mismatches in occlusion and smooth regions.

Depth Estimation Disparity Estimation

NoMorelization: Building Normalizer-Free Models from a Sample's Perspective

no code implementations13 Oct 2022 Chang Liu, Yuwen Yang, Yue Ding, Hongtao Lu

The normalizing layer has become one of the basic configurations of deep learning models, but it still suffers from computational inefficiency, interpretability difficulties, and low generality.

ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation

no code implementations CVPR 2023 Kehan Li, Zhennan Wang, Zesen Cheng, Runyi Yu, Yian Zhao, Guoli Song, Chang Liu, Li Yuan, Jie Chen

Recently, self-supervised large-scale visual pre-training models have shown great promise in representing pixel-level semantic relationships, significantly promoting the development of unsupervised dense prediction tasks, e. g., unsupervised semantic segmentation (USS).

Image Segmentation Unsupervised Semantic Segmentation

Invertible Rescaling Network and Its Extensions

1 code implementation9 Oct 2022 Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu

To be specific, we develop invertible models to generate valid degraded images and meanwhile transform the distribution of lost contents to the fixed distribution of a latent variable during the forward degradation.

Colorization Image Compression

AIA: Attention in Attention Within Collaborate Domains

1 code implementation Pattern Recognition and Computer Vision 2022 Le Zhang, Qi Feng, Yao Lu, Chang Liu, and Guangming Lu

Attention mechanisms can effectively improve the performance of the mobile networks with a limited computational complexity cost.

Deep Attention Position

Time Minimization in Hierarchical Federated Learning

no code implementations7 Oct 2022 Chang Liu, Terence Jie Chua, Jun Zhao

Therefore, we formulate a joint learning and communication optimization problem to minimize total model parameter communication and computation delay, by optimizing local iteration counts and edge iteration counts.

Federated Learning

Robust Bayesian Inference for Moving Horizon Estimation

no code implementations5 Oct 2022 Wenhan Cao, Chang Liu, Zhiqian Lan, Shengbo Eben Li, Wei Pan, Angelo Alessandri

The accuracy of moving horizon estimation (MHE) suffers significantly in the presence of measurement outliers.

Bayesian Inference Combinatorial Optimization

Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-enabled Vehicular Networks

no code implementations26 Sep 2022 Chang Liu, Xuemeng Liu, Shuangyang Li, Weijie Yuan, Derrick Wing Kwan Ng

Predictive beamforming design is an essential task in realizing high-mobility integrated sensing and communication (ISAC), which highly depends on the accuracy of the channel prediction (CP), i. e., predicting the angular parameters of users.

CounTR: Transformer-based Generalised Visual Counting

1 code implementation29 Aug 2022 Chang Liu, Yujie Zhong, Andrew Zisserman, Weidi Xie

In this paper, we consider the problem of generalised visual object counting, with the goal of developing a computational model for counting the number of objects from arbitrary semantic categories, using arbitrary number of "exemplars", i. e. zero-shot or few-shot counting.

Object Counting Self-Supervised Learning

Multimodal Transformer for Automatic 3D Annotation and Object Detection

1 code implementation20 Jul 2022 Chang Liu, Xiaoyan Qian, Binxiao Huang, Xiaojuan Qi, Edmund Lam, Siew-Chong Tan, Ngai Wong

By enriching the sparse point clouds, our method achieves 4. 48\% and 4. 03\% better 3D AP on KITTI moderate and hard samples, respectively, versus the state-of-the-art autolabeler.

3D Object Detection Object +1

$L_2$BN: Enhancing Batch Normalization by Equalizing the $L_2$ Norms of Features

no code implementations6 Jul 2022 Zhennan Wang, Kehan Li, Runyi Yu, Yian Zhao, Pengchong Qiao, Chang Liu, Fan Xu, Xiangyang Ji, Guoli Song, Jie Chen

In this paper, we analyze batch normalization from the perspective of discriminability and find the disadvantages ignored by previous studies: the difference in $l_2$ norms of sample features can hinder batch normalization from obtaining more distinguished inter-class features and more compact intra-class features.

Acoustic Scene Classification Image Classification +1

TANet: Transformer-based Asymmetric Network for RGB-D Salient Object Detection

1 code implementation4 Jul 2022 Chang Liu, Gang Yang, Shuo Wang, Hangxu Wang, Yunhua Zhang, Yutao Wang

We employ the powerful feature extraction capability of Transformer (PVTv2) to extract global semantic information from RGB data and design a lightweight CNN backbone (LWDepthNet) to extract spatial structure information from depth data without pre-training.

object-detection RGB-D Salient Object Detection +1

An Extendable Maneuver Management Framework with Fault-Tolerant Mechanism for Vehicle Platoon Control System in Highway Scenario

no code implementations4 Jul 2022 Chang Liu, Yugong Luo, Pengfei Li, Chunhui Xing, Weiwei Kong

To deal with this problem, this paper introduces a two-dimensional maneuver management framework with a fault-tolerant mechanism on the basis of the proposed hierarchical architecture for the platoon control system.


Tensor Recovery Based on A Novel Non-convex Function Minimax Logarithmic Concave Penalty Function

no code implementations25 Jun 2022 HongBing Zhang, Xinyi Liu, Chang Liu, HongTao Fan, YaJing Li, Xinyun Zhu

The proposed function is generalized to tensor cases, yielding tensor MLCP and weighted tensor $L\gamma$-norm.

Pronunciation Dictionary-Free Multilingual Speech Synthesis by Combining Unsupervised and Supervised Phonetic Representations

no code implementations2 Jun 2022 Chang Liu, Zhen-Hua Ling, Ling-Hui Chen

This paper proposes a multilingual speech synthesis method which combines unsupervised phonetic representations (UPR) and supervised phonetic representations (SPR) to avoid reliance on the pronunciation dictionaries of target languages.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

no code implementations25 May 2022 Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw, Aleš Leonardis, Radu Timofte, Zexin Zhang, Cen Liu, Yunbo Peng, Yue Lin, Gaocheng Yu, Jin Zhang, Zhe Ma, Hongbin Wang, Xiangyu Chen, Xintao Wang, Haiwei Wu, Lin Liu, Chao Dong, Jiantao Zhou, Qingsen Yan, Song Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong, Dan Zhu, Mengdi Sun, Guannan Chen, Yang Hu, Haowei Li, Baozhu Zou, Zhen Liu, Wenjie Lin, Ting Jiang, Chengzhi Jiang, Xinpeng Li, Mingyan Han, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Juan Marín-Vega, Michael Sloth, Peter Schneider-Kamp, Richard Röttger, Chunyang Li, Long Bao, Gang He, Ziyao Xu, Li Xu, Gen Zhan, Ming Sun, Xing Wen, Junlin Li, Shuang Feng, Fei Lei, Rui Liu, Junxiang Ruan, Tianhong Dai, Wei Li, Zhan Lu, Hengyan Liu, Peian Huang, Guangyu Ren, Yonglin Luo, Chang Liu, Qiang Tu, Fangya Li, Ruipeng Gang, Chenghua Li, Jinjing Li, Sai Ma, Chenming Liu, Yizhen Cao, Steven Tel, Barthelemy Heyrman, Dominique Ginhac, Chul Lee, Gahyeon Kim, Seonghyun Park, An Gia Vien, Truong Thanh Nhat Mai, Howoon Yoon, Tu Vo, Alexander Holston, Sheir Zaheer, Chan Y. Park

The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i. e. solutions can not exceed a given number of operations).

Image Restoration Vocal Bursts Intensity Prediction

Test-time Fourier Style Calibration for Domain Generalization

1 code implementation13 May 2022 Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu

Thus, it is still possible that those methods can overfit to source domains and perform poorly on target domains.

Domain Generalization

TTAGN: Temporal Transaction Aggregation Graph Network for Ethereum Phishing Scams Detection

no code implementations28 Apr 2022 Sijia Li, Gaopeng Gou, Chang Liu, Chengshang Hou, Zhenzhen Li, Gang Xiong

In this paper, we propose a Temporal Transaction Aggregation Graph Network (TTAGN) to enhance phishing scams detection performance on Ethereum.

Representation Learning

Instance-Specific Feature Propagation for Referring Segmentation

no code implementations26 Apr 2022 Chang Liu, Xudong Jiang, Henghui Ding

In this work, we propose a novel framework that simultaneously detects the target-of-interest via feature propagation and generates a fine-grained segmentation mask.

Instance Segmentation Segmentation +1

6GAN: IPv6 Multi-Pattern Target Generation via Generative Adversarial Nets with Reinforcement Learning

1 code implementation21 Apr 2022 Tianyu Cui, Gaopeng Gou, Gang Xiong, Chang Liu, Peipei Fu, Zhen Li

6GAN forces multiple generators to train with a multi-class discriminator and an alias detector to generate non-aliased active targets with different addressing pattern types.

Decision Making reinforcement-learning +2

Open-set Text Recognition via Character-Context Decoupling

1 code implementation CVPR 2022 Chang Liu, Chun Yang, Xu-Cheng Yin

Contextual information can be decomposed into temporal information and linguistic information.

Primal-dual Estimator Learning: an Offline Constrained Moving Horizon Estimation Method with Feasibility and Near-optimality Guarantees

no code implementations6 Apr 2022 Wenhan Cao, Jingliang Duan, Shengbo Eben Li, Chen Chen, Chang Liu, Yu Wang

Both the primal and dual estimators are learned from data using supervised learning techniques, and the explicit sample size is provided, which enables us to guarantee the quality of each learned estimator in terms of feasibility and optimality.

MAP-Gen: An Automated 3D-Box Annotation Flow with Multimodal Attention Point Generator

no code implementations29 Mar 2022 Chang Liu, Xiaoyan Qian, Xiaojuan Qi, Edmund Y. Lam, Siew-Chong Tan, Ngai Wong

While a few previous studies tried to automatically generate 3D bounding boxes from weak labels such as 2D boxes, the quality is sub-optimal compared to human annotators.

object-detection Object Detection

Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets

3 code implementations9 Mar 2022 Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu

This technical note describes the recent updates of Graphormer, including architecture design modifications, and the adaption to 3D molecular dynamics simulation.

Benchmarking Graph Regression +1

An Empirical Study of Graphormer on Large-Scale Molecular Modeling Datasets

no code implementations28 Feb 2022 Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu

This technical note describes the recent updates of Graphormer, including architecture design modifications, and the adaption to 3D molecular dynamics simulation.

Time-Frequency Mask Aware Bi-directional LSTM: A Deep Learning Approach for Underwater Acoustic Signal Separation

no code implementations9 Feb 2022 Jie Chen, Chang Liu, Jiawu Xie, Jie An, Nan Huang

In particular, this method breaks through the limitations of the existing methods, not only achieves good results in multivariate separation, but also effectively separates signals when mixed with 40dB Gaussian noise signals.

Temporal Sequences

Direct Molecular Conformation Generation

1 code implementation3 Feb 2022 Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Tao Qin, Wengang Zhou, Houqiang Li, Haiguang Liu, Tie-Yan Liu

Molecular conformation generation aims to generate three-dimensional coordinates of all the atoms in a molecule and is an important task in bioinformatics and pharmacology.

Molecular Docking

Crystal structure prediction with machine learning-based element substitution

1 code implementation26 Jan 2022 Minoru Kusaba, Chang Liu, Ryo Yoshida

The prediction of energetically stable crystal structures formed by a given chemical composition is a central problem in solid-state physics.

BIG-bench Machine Learning Metric Learning

DMF-Net: Dual-Branch Multi-Scale Feature Fusion Network for copy forgery identification of anti-counterfeiting QR code

no code implementations19 Jan 2022 Zhongyuan Guo, Hong Zheng, Changhui You, Tianyu Wang, Chang Liu

We first analyze the production principle of anti-counterfeiting QR code, and convert the identification of copy forgery to device category forensics, and then a Dual-Branch Multi-Scale Feature Fusion network is proposed.

Image Forensics

Recovering Latent Causal Factor for Generalization to Distributional Shifts

1 code implementation NeurIPS 2021 Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu

To avoid such a spurious correlation, we propose \textbf{La}tent \textbf{C}ausal \textbf{I}nvariance \textbf{M}odels (LaCIM) that specifies the underlying causal structure of the data and the source of distributional shifts, guiding us to pursue only causal factor for prediction.

Self-supervised Feature-Gate Coupling for Dynamic Network Pruning

1 code implementation29 Nov 2021 Mengnan Shi, Chang Liu, Jianbin Jiao, Qixiang Ye

Gating modules have been widely explored in dynamic network pruning to reduce the run-time computational cost of deep neural networks while preserving the representation of features.

Contrastive Learning Network Pruning

Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification

no code implementations20 Nov 2021 Long Gao, Chang Liu, Dooman Arefan, Ashok Panigrahy, Margarita L. Zuley, Shandong Wu

To address this challenge, we propose a medical-knowledge-guided one-class classification approach that leverages domain-specific knowledge of classification tasks to boost the model's performance.

Image Classification Medical Image Classification +1