Search Results for author: Liang Li

Found 93 papers, 43 papers with code

Unifying Structured Data as Graph for Data-to-Text Pre-Training

1 code implementation2 Jan 2024 Shujie Li, Liang Li, Ruiying Geng, Min Yang, Binhua Li, Guanghu Yuan, Wanwei He, Shao Yuan, Can Ma, Fei Huang, Yongbin Li

In this paper, we unify different types of structured data (i. e., table, key-value data, knowledge graph) into the graph format and cast different data-to-text generation tasks as graph-to-text generation.

Data-to-Text Generation

Hard Sample Aware Network for Contrastive Deep Graph Clustering

2 code implementations16 Dec 2022 Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, Jingcan Duan, Cancan Chen

Moreover, under the guidance of the carefully collected high-confidence clustering information, our proposed weight modulating function will first recognize the positive and negative samples and then dynamically up-weight the hard sample pairs while down-weighting the easy ones.

Attribute Clustering +1

FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset

1 code implementation CVPR 2022 Lizhen Wang, ZhiYuan Chen, Tao Yu, Chenguang Ma, Liang Li, Yebin Liu

In the coarse module, we generate a base parametric model from large-scale RGB-D images, which is able to predict accurate rough 3D face models in different genders, ages, etc.

3D Face Reconstruction Face Model

Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations

2 code implementations CVPR 2020 Shuhao Cui, Shuhui Wang, Junbao Zhuo, Liang Li, Qingming Huang, Qi Tian

We find by theoretical analysis that the prediction discriminability and diversity could be separately measured by the Frobenius-norm and rank of the batch output matrix.

Domain Adaptation

Fast Batch Nuclear-norm Maximization and Minimization for Robust Domain Adaptation

1 code implementation13 Jul 2021 Shuhao Cui, Shuhui Wang, Junbao Zhuo, Liang Li, Qingming Huang, Qi Tian

Due to the domain discrepancy in visual domain adaptation, the performance of source model degrades when bumping into the high data density near decision boundary in target domain.

Domain Adaptation

Learning to Dub Movies via Hierarchical Prosody Models

1 code implementation CVPR 2023 Gaoxiang Cong, Liang Li, Yuankai Qi, ZhengJun Zha, Qi Wu, Wenyu Wang, Bin Jiang, Ming-Hsuan Yang, Qingming Huang

Given a piece of text, a video clip and a reference audio, the movie dubbing (also known as visual voice clone V2C) task aims to generate speeches that match the speaker's emotion presented in the video using the desired speaker voice as reference.

Comparing Representations in Tracking for Event Camera-based SLAM

1 code implementation20 Apr 2021 Jianhao Jiao, Huaiyang Huang, Liang Li, Zhijian He, Yilong Zhu, Ming Liu

This paper investigates two typical image-type representations for event camera-based tracking: time surface (TS) and event map (EM).

Rethinking Graph Neural Architecture Search from Message-passing

1 code implementation CVPR 2021 Shaofei Cai, Liang Li, Jincan Deng, Beichen Zhang, Zheng-Jun Zha, Li Su, Qingming Huang

Inspired by the strong searching capability of neural architecture search (NAS) in CNN, this paper proposes Graph Neural Architecture Search (GNAS) with novel-designed search space.

feature selection Neural Architecture Search

Few Shot Generative Model Adaption via Relaxed Spatial Structural Alignment

2 code implementations CVPR 2022 Jiayu Xiao, Liang Li, Chaofei Wang, Zheng-Jun Zha, Qingming Huang

A feasible solution is to start with a GAN well-trained on a large scale source domain and adapt it to the target domain with a few samples, termed as few shot generative model adaption.

Generative Adversarial Network

Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive Environments

1 code implementation11 May 2020 Baiming Chen, Mengdi Xu, Zuxin Liu, Liang Li, Ding Zhao

We also test the proposed algorithm in traffic scenarios that require coordination of all autonomous vehicles to show the practical value of delay-awareness.

Autonomous Vehicles Multi-agent Reinforcement Learning +2

TreeBERT: A Tree-Based Pre-Trained Model for Programming Language

1 code implementation26 May 2021 Xue Jiang, Zhuoran Zheng, Chen Lyu, Liang Li, Lei Lyu

In this paper, we present TreeBERT, a tree-based pre-trained model for improving programming language-oriented generation tasks.

Code Summarization Language Modelling +1

LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection

1 code implementation29 Jan 2024 Sifan Zhou, Liang Li, Xinyu Zhang, Bo Zhang, Shipeng Bai, Miao Sun, Ziyu Zhao, Xiaobo Lu, Xiangxiang Chu

To our knowledge, for the very first time in lidar-based 3D detection tasks, the PTQ INT8 model's accuracy is almost the same as the FP32 model while enjoying $3\times$ inference speedup.

3D Object Detection Autonomous Vehicles +3

Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding

1 code implementation ICCV 2019 Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha, Dechao Meng, Qingming Huang

It builds the correspondence between image region proposal and query in an adaptive manner: adaptive grounding and collaborative reconstruction.

Attribute Referring Expression +1

Automatic Relation-aware Graph Network Proliferation

1 code implementation CVPR 2022 Shaofei Cai, Liang Li, Xinzhe Han, Jiebo Luo, Zheng-Jun Zha, Qingming Huang

However, the currently used graph search space overemphasizes learning node features and neglects mining hierarchical relational information.

Graph Classification Graph Learning +5

Local Sample-weighted Multiple Kernel Clustering with Consensus Discriminative Graph

1 code implementation5 Jul 2022 Liang Li, Siwei Wang, Xinwang Liu, En Zhu, Li Shen, Kenli Li, Keqin Li

Multiple kernel clustering (MKC) is committed to achieving optimal information fusion from a set of base kernels.

Clustering

EpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting

1 code implementation23 Aug 2022 Feng Xie, Zhong Zhang, Liang Li, Bin Zhou, Yusong Tan

Epidemic forecasting is the key to effective control of epidemic transmission and helps the world mitigate the crisis that threatens public health.

Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking

2 code implementations CVPR 2020 Jin Gao, Yan Lu, Xiaojuan Qi, Yutong Kou, Bing Li, Liang Li, Shan Yu, Weiming Hu

In this paper, we propose a simple yet effective recursive least-squares estimator-aided online learning approach for few-shot online adaptation without requiring offline training.

Continual Learning One-Shot Learning +1

Machine Discovery of Partial Differential Equations from Spatiotemporal Data

1 code implementation15 Sep 2019 Ye Yuan, Junlin Li, Liang Li, Frank Jiang, Xiuchuan Tang, Fumin Zhang, Sheng Liu, Jorge Goncalves, Henning U. Voss, Xiuting Li, Jürgen Kurths, Han Ding

The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data.

ZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking

1 code implementation NeurIPS 2023 Yutong Kou, Jin Gao, Bing Li, Gang Wang, Weiming Hu, Yizheng Wang, Liang Li

To this end, we non-uniformly resize the cropped image to have a smaller input size while the resolution of the area where the target is more likely to appear is higher and vice versa.

Visual Tracking

Calibrated Feature Decomposition for Generalizable Person Re-Identification

1 code implementation27 Nov 2021 Kecheng Zheng, Jiawei Liu, Wei Wu, Liang Li, Zheng-Jun Zha

The calibrated person representation is subtly decomposed into the identity-relevant feature, domain feature, and the remaining entangled one.

Domain Generalization Generalizable Person Re-identification

Neighborhood Contrastive Transformer for Change Captioning

1 code implementation6 Mar 2023 Yunbin Tu, Liang Li, Li Su, Ke Lu, Qingming Huang

Change captioning is to describe the semantic change between a pair of similar images in natural language.

Image Captioning

R$^3$Net:Relation-embedded Representation Reconstruction Network for Change Captioning

1 code implementation20 Oct 2021 Yunbin Tu, Liang Li, Chenggang Yan, Shengxiang Gao, Zhengtao Yu

In this paper, we propose a Relation-embedded Representation Reconstruction Network (R$^3$Net) to explicitly distinguish the real change from the large amount of clutter and irrelevant changes.

Relation Sentence

Rˆ3Net:Relation-embedded Representation Reconstruction Network for Change Captioning

1 code implementation EMNLP 2021 Yunbin Tu, Liang Li, Chenggang Yan, Shengxiang Gao, Zhengtao Yu

In this paper, we propose a Relation-embedded Representation Reconstruction Network (Rˆ3Net) to explicitly distinguish the real change from the large amount of clutter and irrelevant changes.

Relation Sentence

Separate and Locate: Rethink the Text in Text-based Visual Question Answering

1 code implementation31 Aug 2023 Chengyang Fang, Jiangnan Li, Liang Li, Can Ma, Dayong Hu

To tackle these problems, we propose a novel method named Separate and Locate (SaL) that explores text contextual cues and designs spatial position embedding to construct spatial relations between OCR texts.

Optical Character Recognition (OCR) Position +3

Knowledge-guided Pairwise Reconstruction Network for Weakly Supervised Referring Expression Grounding

1 code implementation5 Sep 2019 Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha, Li Su, Qingming Huang

Weakly supervised referring expression grounding (REG) aims at localizing the referential entity in an image according to linguistic query, where the mapping between the image region (proposal) and the query is unknown in the training stage.

Object Referring Expression +2

Plan-then-Seam: Towards Efficient Table-to-Text Generation

1 code implementation10 Feb 2023 Liang Li, Ruiying Geng, Chengyang Fang, Bing Li, Can Ma, Binhua Li, Yongbin Li

Table-to-text generation aims at automatically generating text to help people conveniently obtain salient information in tables.

Table-to-Text Generation

Context Disentangling and Prototype Inheriting for Robust Visual Grounding

1 code implementation19 Dec 2023 Wei Tang, Liang Li, Xuejing Liu, Lu Jin, Jinhui Tang, Zechao Li

In this paper, we propose a novel framework with context disentangling and prototype inheriting for robust visual grounding to handle both scenes.

Visual Grounding

State-Relabeling Adversarial Active Learning

1 code implementation CVPR 2020 Beichen Zhang, Liang Li, Shijie Yang, Shuhui Wang, Zheng-Jun Zha, Qingming Huang

In this paper, we propose a state relabeling adversarial active learning model (SRAAL), that leverages both the annotation and the labeled/unlabeled state information for deriving the most informative unlabeled samples.

Active Learning

LS-GAN: Iterative Language-based Image Manipulation via Long and Short Term Consistency Reasoning

2 code implementations journal 2022 Gaoxiang Cong, Liang Li, Zhenhuan Liu, Yunbin Tu, Weijun Qin, Shenyuan Zhang, Chengang Yan, Wenyu Wang, Bin Jiang

To address this issue, we propose a novel Long and Short term consistency reasoning Generative Adversarial Network (LS-GAN), which enhances the awareness of previous objects with current instruction and better maintains the consistency with the user's intent under the continuous iterations.

Generative Adversarial Network Image Manipulation

Entity-enhanced Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding

1 code implementation18 Jul 2022 Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha, Zechao Li, Qi Tian, Qingming Huang

Second, most previous weakly supervised REG methods ignore the discriminative location and context of the referent, causing difficulties in distinguishing the target from other same-category objects.

Attribute Referring Expression +2

Text-Driven Generative Domain Adaptation with Spectral Consistency Regularization

1 code implementation ICCV 2023 Zhenhuan Liu, Liang Li, Jiayu Xiao, Zheng-Jun Zha, Qingming Huang

The experiments demonstrate the effectiveness of our method to preserve the diversity of source domain and generate high fidelity target images.

Domain Adaptation

Image Prediction for Limited-angle Tomography via Deep Learning with Convolutional Neural Network

no code implementations29 Jul 2016 Hanming Zhang, Liang Li, Kai Qiao, Linyuan Wang, Bin Yan, Lei LI, Guoen Hu

The qualitative and quantitative evaluations of experimental results indicate that the proposed method show a stable and prospective performance on artifacts reduction and detail recovery for limited angle tomography.

Computed Tomography (CT)

An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as An Example

no code implementations12 Sep 2018 Yuanzhe Yao, Zeheng Wang, Liang Li, Kun Lu, Runyu Liu, Zhiyuan Liu, Jing Yan

In this work, an ontology-based model for AI-assisted medicine side-effect (SE) prediction is developed, where three main components, including the drug model, the treatment model, and the AI-assisted prediction model, of proposed model are presented.

Fast OBDD Reordering using Neural Message Passing on Hypergraph

no code implementations6 Nov 2018 Feifan Xu, Fei He, Enze Xie, Liang Li

Ordered binary decision diagrams (OBDDs) are an efficient data structure for representing and manipulating Boolean formulas.

A Self-Attentive Model with Gate Mechanism for Spoken Language Understanding

no code implementations EMNLP 2018 Changliang Li, Liang Li, Ji Qi

In this work, we propose a novel self-attentive model with gate mechanism to fully utilize the semantic correlation between slot and intent.

Automatic Speech Recognition (ASR) Intent Detection +5

Maximum Cohesive Grid of Superpixels for Fast Object Localization

no code implementations CVPR 2013 Liang Li, Wei Feng, Liang Wan, Jiawan Zhang

For this purpose, we aim at constructing maximum cohesive SP-grid, which is composed of real nodes, i. e. SPs, and dummy nodes that are meaningless in the image with only position-taking function in the grid.

Object Object Localization +1

Image Classification base on PCA of Multi-view Deep Representation

no code implementations12 Mar 2019 Yaoqi Sun, Liang Li, Liang Zheng, Ji Hu, Yatong Jiang, Chenggang Yan

In the age of information explosion, image classification is the key technology of dealing with and organizing a large number of image data.

Classification General Classification +1

Low rank tensor completion with sparse regularization in a transformed domain

no code implementations19 Nov 2019 Ping-Ping Wang, Liang Li, Guang-Hui Cheng

While the sparse regularizer is imposed by a $\ell_{1}$-norm in a discrete cosine transformation (DCT) domain, which can better employ the local sparse property of completed data.

Meta-Learning PAC-Bayes Priors in Model Averaging

no code implementations24 Dec 2019 Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li

In this paper, we mainly consider the scenario in which we have a common model set used for model averaging instead of selecting a single final model via a model selection procedure to account for this model's uncertainty to improve the reliability and accuracy of inferences.

Meta-Learning Model Selection

Secure Social Recommendation based on Secret Sharing

no code implementations6 Feb 2020 Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou

It is well known that social information, which is rich on social platforms such as Facebook, are useful to recommender systems.

Privacy Preserving Recommendation Systems

Real-world Person Re-Identification via Degradation Invariance Learning

no code implementations CVPR 2020 Yukun Huang, Zheng-Jun Zha, Xueyang Fu, Richang Hong, Liang Li

Person re-identification (Re-ID) in real-world scenarios usually suffers from various degradation factors, e. g., low-resolution, weak illumination, blurring and adverse weather.

Image Restoration Person Re-Identification +2

Secret Sharing based Secure Regressions with Applications

no code implementations10 Apr 2020 Chaochao Chen, Liang Li, Wenjing Fang, Jun Zhou, Li Wang, Lei Wang, Shuang Yang, Alex Liu, Hao Wang

Nowadays, the utilization of the ever expanding amount of data has made a huge impact on web technologies while also causing various types of security concerns.

regression

Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios

no code implementations14 Apr 2020 Baiming Chen, Xiang Chen, Wu Qiong, Liang Li

Results show that the adversarial scenarios generated by our method significantly degrade the performance of the tested vehicles.

Autonomous Driving

Learning Better Representation for Tables by Self-Supervised Tasks

no code implementations15 Oct 2020 Liang Li, Can Ma, Yinliang Yue, Linjun Shou, Dayong Hu

Secondly, the target texts in training dataset may contain redundant information or facts do not exist in the input tables.

Table-to-Text Generation

TDRE: A Tensor Decomposition Based Approach for Relation Extraction

no code implementations15 Oct 2020 Bin-Bin Zhao, Liang Li, Hui-Dong Zhang

Extracting entity pairs along with relation types from unstructured texts is a fundamental subtask of information extraction.

Relation Relation Classification +2

Artificial Lateral Line Based Relative State Estimation for Two Adjacent Robotic Fish

no code implementations23 Jun 2020 Xingwen Zheng, Wei Wang, Liang Li, Guangming Xie

Then four typical regression methods, including random forest algorithm, support vector regression, back propagation neural network, and multiple linear regression method are used for establishing regression models between the ALLS-measured HPVs and the relative states.

regression

Energy Efficient Federated Learning over Heterogeneous Mobile Devices via Joint Design of Weight Quantization and Wireless Transmission

no code implementations21 Dec 2020 Rui Chen, Liang Li, Kaiping Xue, Chi Zhang, Miao Pan, Yuguang Fang

To address these challenges, in this paper, we attempt to take FL into the design of future wireless networks and develop a novel joint design of wireless transmission and weight quantization for energy efficient FL over mobile devices.

Edge-computing Federated Learning +1

To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices

no code implementations22 Dec 2020 Liang Li, Dian Shi, Ronghui Hou, Hui Li, Miao Pan, Zhu Han

Recent advances in machine learning, wireless communication, and mobile hardware technologies promisingly enable federated learning (FL) over massive mobile edge devices, which opens new horizons for numerous intelligent mobile applications.

Federated Learning

Towards Energy Efficient Federated Learning over 5G+ Mobile Devices

no code implementations13 Jan 2021 Dian Shi, Liang Li, Rui Chen, Pavana Prakash, Miao Pan, Yuguang Fang

The continuous convergence of machine learning algorithms, 5G and beyond (5G+) wireless communications, and artificial intelligence (AI) hardware implementation hastens the birth of federated learning (FL) over 5G+ mobile devices, which pushes AI functions to mobile devices and initiates a new era of on-device AI applications.

Federated Learning Quantization

Manipulating the anisotropic phase separation in strained VO2 epitaxial films by nanoscale ion-implantation

no code implementations18 Jan 2021 Changlong Hu, Liang Li, Xiaolei Wen, Yuliang Chen, Bowen Li, Hui Ren, Shanguang Zhao, Chongwen Zou

Manipulating the strain induced poly-domains and phase transition in correlated oxide material are important for high performance devices fabrication.

Materials Science Strongly Correlated Electrons

Dissecting Energy Budget of a Gamma-Ray Burst Fireball

no code implementations9 Feb 2021 Bing Zhang, Yu Wang, Liang Li

The jet composition and radiative efficiency of GRBs are poorly constrained from the data.

High Energy Astrophysical Phenomena

Improving Semiconductor Device Modeling for Electronic Design Automation by Machine Learning Techniques

no code implementations25 May 2021 Zeheng Wang, Liang Li, Ross C. C. Leon, Jinlin Yang, Junjie Shi, Timothy van der Laan, Muhammad Usman

The inherent flexibility of our approach allows easy adaptation to various tasks, thus making it highly relevant to many applications of the semiconductor industry.

BIG-bench Machine Learning

Structured Multi-Level Interaction Network for Video Moment Localization via Language Query

no code implementations CVPR 2021 Hao Wang, Zheng-Jun Zha, Liang Li, Dong Liu, Jiebo Luo

In particular, for cross-modal interaction, we interact the sentence-level query with the whole moment while interact the word-level query with content and boundary, as in a coarse-to-fine manner.

Sentence

Multi-Modulation Network for Audio-Visual Event Localization

no code implementations26 Aug 2021 Hao Wang, Zheng-Jun Zha, Liang Li, Xuejin Chen, Jiebo Luo

We propose a novel MultiModulation Network (M2N) to learn the above correlation and leverage it as semantic guidance to modulate the related auditory, visual, and fused features.

audio-visual event localization

Edge-featured Graph Neural Architecture Search

no code implementations3 Sep 2021 Shaofei Cai, Liang Li, Xinzhe Han, Zheng-Jun Zha, Qingming Huang

Recently, researchers study neural architecture search (NAS) to reduce the dependence of human expertise and explore better GNN architectures, but they over-emphasize entity features and ignore latent relation information concealed in the edges.

Neural Architecture Search

Modality-Adaptive Mixup and Invariant Decomposition for RGB-Infrared Person Re-Identification

no code implementations3 Mar 2022 Zhipeng Huang, Jiawei Liu, Liang Li, Kecheng Zheng, Zheng-Jun Zha

RGB-infrared person re-identification is an emerging cross-modality re-identification task, which is very challenging due to significant modality discrepancy between RGB and infrared images.

Person Re-Identification

Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification

no code implementations3 Mar 2022 Jiawei Liu, Zhipeng Huang, Liang Li, Kecheng Zheng, Zheng-Jun Zha

In this paper, we propose a novel Debiased Batch Normalization via Gaussian Process approach (GDNorm) for generalizable person re-identification, which models the feature statistic estimation from BN layers as a dynamically self-refining Gaussian process to alleviate the bias to unseen domain for improving the generalization.

Generalizable Person Re-identification Representation Learning

Unsupervised Coherent Video Cartoonization with Perceptual Motion Consistency

1 code implementation2 Apr 2022 Zhenhuan Liu, Liang Li, Huajie Jiang, Xin Jin, Dandan Tu, Shuhui Wang, Zheng-Jun Zha

Furthermore, we devise the spatio-temporal correlative map as a style-independent, global-aware regularization on the perceptual motion consistency.

Optical Flow Estimation Style Transfer

Adaptive Structural Similarity Preserving for Unsupervised Cross Modal Hashing

no code implementations9 Jul 2022 Liang Li, Baihua Zheng, Weiwei Sun

We introduce structural semantic metrics based on graph adjacency relations during the semantic reconstruction and correlation mining stage and meanwhile align the structure semantics in the hash space with an asymmetric binary optimization process.

Management Representation Learning

Cross-Architecture Knowledge Distillation

no code implementations12 Jul 2022 Yufan Liu, Jiajiong Cao, Bing Li, Weiming Hu, Jingting Ding, Liang Li

However, most existing knowledge distillation methods only consider homologous-architecture distillation, such as distilling knowledge from CNN to CNN.

Knowledge Distillation

Multiple Kernel Clustering with Dual Noise Minimization

no code implementations13 Jul 2022 Junpu Zhang, Liang Li, Siwei Wang, Jiyuan Liu, Yue Liu, Xinwang Liu, En Zhu

As a representative, late fusion MKC first decomposes the kernels into orthogonal partition matrices, then learns a consensus one from them, achieving promising performance recently.

Clustering

DSPNet: Towards Slimmable Pretrained Networks based on Discriminative Self-supervised Learning

no code implementations13 Jul 2022 Shaoru Wang, Zeming Li, Jin Gao, Liang Li, Weiming Hu

However, when facing various resource budgets in real-world applications, it costs a huge computation burden to pretrain multiple networks of various sizes one by one.

Knowledge Distillation Self-Supervised Learning

Energy and Spectrum Efficient Federated Learning via High-Precision Over-the-Air Computation

no code implementations15 Aug 2022 Liang Li, Chenpei Huang, Dian Shi, Hao Wang, Xiangwei Zhou, Minglei Shu, Miao Pan

Guided by FL convergence analysis, we formulate a joint transmission probability and local computing control optimization, aiming to minimize the overall energy consumption (i. e., iterative local computing + multi-round communications) of mobile devices in FL.

Federated Learning

Make RepVGG Greater Again: A Quantization-aware Approach

2 code implementations3 Dec 2022 Xiangxiang Chu, Liang Li, Bo Zhang

Nonetheless, its quantization performance is usually too poor to deploy (more than 20% top-1 accuracy drop on ImageNet) when INT8 inference is desired.

Quantization Semantic Segmentation

Protective Self-Adaptive Pruning to Better Compress DNNs

no code implementations21 Mar 2023 Liang Li, Pengfei Zhao

Adaptive network pruning approach has recently drawn significant attention due to its excellent capability to identify the importance and redundancy of layers and filters and customize a suitable pruning solution.

Network Pruning

Decoupling-and-Aggregating for Image Exposure Correction

no code implementations CVPR 2023 Yang Wang, Long Peng, Liang Li, Yang Cao, Zheng-Jun Zha

To this end, we inject the addition/difference operation into the convolution process and devise a Contrast Aware (CA) unit and a Detail Aware (DA) unit to facilitate the statistical and structural regularities modeling.

CATS: A Pragmatic Chinese Answer-to-Sequence Dataset with Large Scale and High Quality

no code implementations20 Jun 2023 Liang Li, Ruiying Geng, Chengyang Fang, Bing Li, Can Ma, Rongyu Cao, Binhua Li, Fei Huang, Yongbin Li

To alleviate these limitations, in this paper, we present CATS, a pragmatic Chinese answer-to-sequence dataset with large scale and high quality.

Predator-prey survival pressure is sufficient to evolve swarming behaviors

no code implementations24 Aug 2023 Jianan Li, Liang Li, Shiyu Zhao

The comprehension of how local interactions arise in global collective behavior is of utmost importance in both biological and physical research.

reinforcement-learning

FPTQ: Fine-grained Post-Training Quantization for Large Language Models

no code implementations30 Aug 2023 Qingyuan Li, Yifan Zhang, Liang Li, Peng Yao, Bo Zhang, Xiangxiang Chu, Yerui Sun, Li Du, Yuchen Xie

In this study, we propose a novel W4A8 post-training quantization method for the available open-sourced LLMs, which combines the advantages of both two recipes.

Quantization

Norm Tweaking: High-performance Low-bit Quantization of Large Language Models

no code implementations6 Sep 2023 Liang Li, Qingyuan Li, Bo Zhang, Xiangxiang Chu

On GLM-130B and OPT-66B, our method even achieves the same level of accuracy at 2-bit quantization as their float ones.

Model Compression Quantization

KDD-LOAM: Jointly Learned Keypoint Detector and Descriptors Assisted LiDAR Odometry and Mapping

no code implementations27 Sep 2023 Renlang Huang, Minglei Zhao, Jiming Chen, Liang Li

Sparse keypoint matching based on distinct 3D feature representations can improve the efficiency and robustness of point cloud registration.

Point Cloud Registration Self-Supervised Learning

SAGE-ICP: Semantic Information-Assisted ICP

no code implementations11 Oct 2023 Jiaming Cui, Jiming Chen, Liang Li

Robust and accurate pose estimation in unknown environments is an essential part of robotic applications.

Pose Estimation

R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generation

no code implementations13 Oct 2023 Jiayu Xiao, Henglei Lv, Liang Li, Shuhui Wang, Qingming Huang

Recent text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images given text-prompts as input.

Text-to-Image Generation

Pick-and-Draw: Training-free Semantic Guidance for Text-to-Image Personalization

no code implementations30 Jan 2024 Henglei Lv, Jiayu Xiao, Liang Li, Qingming Huang

To this end, we propose Pick-and-Draw, a training-free semantic guidance approach to boost identity consistency and generative diversity for personalization methods.

StyleDubber: Towards Multi-Scale Style Learning for Movie Dubbing

no code implementations20 Feb 2024 Gaoxiang Cong, Yuankai Qi, Liang Li, Amin Beheshti, Zhedong Zhang, Anton Van Den Hengel, Ming-Hsuan Yang, Chenggang Yan, Qingming Huang

It contains three main components: (1) A multimodal style adaptor operating at the phoneme level to learn pronunciation style from the reference audio, and generate intermediate representations informed by the facial emotion presented in the video; (2) An utterance-level style learning module, which guides both the mel-spectrogram decoding and the refining processes from the intermediate embeddings to improve the overall style expression; And (3) a phoneme-guided lip aligner to maintain lip sync.

Voice Cloning

Emergency Caching: Coded Caching-based Reliable Map Transmission in Emergency Networks

no code implementations27 Feb 2024 Zeyu Tian, Lianming Xu, Liang Li, Li Wang, Aiguo Fei

In this study, we propose a three-layer architecture of emergency caching networks focusing on data collection and reliable transmission, by leveraging efficient perception and edge caching technologies.

Decision Making

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