Search Results for author: Liu Liu

Found 60 papers, 14 papers with code

Boosting Deep Neural Network Efficiency with Dual-Module Inference

no code implementations ICML 2020 Liu Liu, Lei Deng, Zhaodong Chen, yuke wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie

Using Deep Neural Networks (DNNs) in machine learning tasks is promising in delivering high-quality results but challenging to meet stringent latency requirements and energy constraints because of the memory-bound and the compute-bound execution pattern of DNNs.

Deep Streaming Label Learning

no code implementations ICML 2020 Zhen Wang, Liu Liu, DaCheng Tao

In order to fill in these research gaps, we propose a novel deep neural network (DNN) based framework, Deep Streaming Label Learning (DSLL), to classify instances with newly emerged labels effectively.

Multi-Label Learning

Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels

no code implementations NeurIPS 2021 Sheng Wan, Yibing Zhan, Liu Liu, Baosheng Yu, Shirui Pan, Chen Gong

Essentially, our CGPN can enhance the learning performance of GNNs under extremely limited labels by contrastively propagating the limited labels to the entire graph.

Graph Attention Node Classification +1

Transformer Acceleration with Dynamic Sparse Attention

no code implementations21 Oct 2021 Liu Liu, Zheng Qu, Zhaodong Chen, Yufei Ding, Yuan Xie

We demonstrate that the sparse patterns are dynamic, depending on input sequences.

Lagrangian Generative Adversarial Imitation Learning with Safety

no code implementations29 Sep 2021 Zhihao Cheng, Li Shen, Meng Fang, Liu Liu, DaCheng Tao

Imitation Learning (IL) merely concentrates on reproducing expert behaviors and could take dangerous actions, which is unbearable in safety-critical scenarios.

Imitation Learning

Multi-modal Affect Analysis using standardized data within subjects in the Wild

no code implementations7 Jul 2021 Sachihiro Youoku, Takahisa Yamamoto, Junya Saito, Akiyoshi Uchida, Xiaoyu Mi, Ziqiang Shi, Liu Liu, Zhongling Liu, Osafumi Nakayama, Kentaro Murase

Therefore, after learning the common features for each frame, we constructed a facial expression estimation model and valence-arousal model using time-series data after combining the common features and the standardized features for each video.

Time Series

OPA: Object Placement Assessment Dataset

1 code implementation5 Jul 2021 Liu Liu, Bo Zhang, Jiangtong Li, Li Niu, Qingyang Liu, Liqing Zhang

Image composition aims to generate realistic composite image by inserting an object from one image into another background image, where the placement (e. g., location, size, occlusion) of inserted object may be unreasonable, which would significantly degrade the quality of the composite image.

Making Images Real Again: A Comprehensive Survey on Deep Image Composition

1 code implementation28 Jun 2021 Li Niu, Wenyan Cong, Liu Liu, Yan Hong, Bo Zhang, Jing Liang, Liqing Zhang

Datasets and codes for image composition are summarized at https://github. com/bcmi/Awesome-Image-Composition.

PluckerNet: Learn To Register 3D Line Reconstructions

no code implementations CVPR 2021 Liu Liu, Hongdong Li, Haodong Yao, Ruyi Zha

Aligning two partially-overlapped 3D line reconstructions in Euclidean space is challenging, as we need to simultaneously solve line correspondences and relative pose between reconstructions.

Translation

Towards Real-World Category-level Articulation Pose Estimation

no code implementations7 May 2021 Liu Liu, Han Xue, Wenqiang Xu, Haoyuan Fu, Cewu Lu

This setting allows varied kinematic structures within a semantic category, and multiple instances to co-exist in an observation of real world.

Mixed Reality Pose Estimation

A deep neural network approach on solving the linear transport model under diffusive scaling

no code implementations24 Feb 2021 Liu Liu, Tieyong Zeng, Zecheng Zhang

In our framework, the solution is approximated by a neural network that satisfies both the governing equation and other constraints.

Numerical Analysis Numerical Analysis

Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation

1 code implementation19 Jan 2021 Ye Huang, Di Kang, Wenjing Jia, Xiangjian He, Liu Liu

Spatial and channel attentions, modelling the semantic interdependencies in spatial and channel dimensions respectively, have recently been widely used for semantic segmentation.

Semantic Segmentation

Semantic Inference Network for Few-shot Streaming Label Learning

no code implementations1 Jan 2021 Zhen Wang, Liu Liu, Yiqun Duan, DaCheng Tao

In this work, we formulate and study few-shot streaming label learning (FSLL), which models emerging new labels with only a few annotated examples by utilizing the knowledge learned from past labels.

Meta-Learning Multi-Label Classification

Adaptive Curriculum Learning

no code implementations ICCV 2021 Yajing Kong, Liu Liu, Jun Wang, DaCheng Tao

Therefore, in contrast to recent works using a fixed curriculum, we devise a new curriculum learning method, Adaptive Curriculum Learning (Adaptive CL), adapting the difficulty of examples to the current state of the model.

Curriculum Learning

PlueckerNet: Learn to Register 3D Line Reconstructions

1 code implementation2 Dec 2020 Liu Liu, Hongdong Li, Haodong Yao, Ruyi Zha

Aligning two partially-overlapped 3D line reconstructions in Euclidean space is challenging, as we need to simultaneously solve correspondences and relative pose between line reconstructions.

Translation

On the Guaranteed Almost Equivalence between Imitation Learning from Observation and Demonstration

no code implementations16 Oct 2020 Zhihao Cheng, Liu Liu, Aishan Liu, Hao Sun, Meng Fang, DaCheng Tao

By contrast, this paper proves that LfO is almost equivalent to LfD in the deterministic robot environment, and more generally even in the robot environment with bounded randomness.

Imitation Learning

Weak-shot Fine-grained Classification via Similarity Transfer

1 code implementation NeurIPS 2021 Junjie Chen, Li Niu, Liu Liu, Liqing Zhang

In this setting, we propose a method called SimTrans to transfer pairwise semantic similarity from base categories to novel categories.

Classification General Classification +2

Solving the Blind Perspective-n-Point Problem End-To-End With Robust Differentiable Geometric Optimization

2 code implementations ECCV 2020 Dylan Campbell, Liu Liu, Stephen Gould

We instead propose the first fully end-to-end trainable network for solving the blind PnP problem efficiently and globally, that is, without the need for pose priors.

Robust Compressed Sensing using Generative Models

1 code implementation NeurIPS 2020 Ajil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis

In analogy to classical compressed sensing, here we assume a generative model as a prior, that is, we assume the vector is represented by a deep generative model $G: \mathbb{R}^k \rightarrow \mathbb{R}^n$.

Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution

no code implementations CVPR 2020 Xibin Song, Yuchao Dai, Dingfu Zhou, Liu Liu, Wei Li, Hongdng Li, Ruigang Yang

Second, we propose a new framework for real-world DSR, which consists of four modules : 1) An iterative residual learning module with deep supervision to learn effective high-frequency components of depth maps in a coarse-to-fine manner; 2) A channel attention strategy to enhance channels with abundant high-frequency components; 3) A multi-stage fusion module to effectively re-exploit the results in the coarse-to-fine process; and 4) A depth refinement module to improve the depth map by TGV regularization and input loss.

Depth Map Super-Resolution

Computation on Sparse Neural Networks: an Inspiration for Future Hardware

no code implementations24 Apr 2020 Fei Sun, Minghai Qin, Tianyun Zhang, Liu Liu, Yen-Kuang Chen, Yuan Xie

We show that for practically complicated problems, it is more beneficial to search large and sparse models in the weight dominated region.

Learning 2D-3D Correspondences To Solve The Blind Perspective-n-Point Problem

1 code implementation15 Mar 2020 Liu Liu, Dylan Campbell, Hongdong Li, Dingfu Zhou, Xibin Song, Ruigang Yang

Conventional absolute camera pose via a Perspective-n-Point (PnP) solver often assumes that the correspondences between 2D image pixels and 3D points are given.

Spatial-Aware Feature Aggregation for Image based Cross-View Geo-Localization

1 code implementation NeurIPS 2019 Yujiao Shi, Liu Liu, Xin Yu, Hongdong Li

The first step is to apply a regular polar transform to warp an aerial image such that its domain is closer to that of a ground-view panorama.

DoveNet: Deep Image Harmonization via Domain Verification

1 code implementation CVPR 2020 Wenyan Cong, Jianfu Zhang, Li Niu, Liu Liu, Zhixin Ling, Weiyuan Li, Liqing Zhang

Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image.

Dual-module Inference for Efficient Recurrent Neural Networks

no code implementations25 Sep 2019 Liu Liu, Lei Deng, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie

Using Recurrent Neural Networks (RNNs) in sequence modeling tasks is promising in delivering high-quality results but challenging to meet stringent latency requirements because of the memory-bound execution pattern of RNNs.

Quantum algorithm for finding the negative curvature direction

no code implementations25 Sep 2019 Kaining Zhang, Min-Hsiu Hsieh, Liu Liu, DaCheng Tao

Moreover, we propose an efficient algorithm to achieve the classical read-out of the target state.

Stochastically Controlled Compositional Gradient for the Composition problem

no code implementations25 Sep 2019 Liu Liu, Ji Liu, Cho-Jui Hsieh, DaCheng Tao

The strategy is also accompanied by a mini-batch version of the proposed method that improves query complexity with respect to the size of the mini-batch.

Encoding Selection for Solving Hamiltonian Cycle Problems with ASP

no code implementations18 Sep 2019 Liu Liu, Miroslaw Truszczynski

It is common for search and optimization problems to have alternative equivalent encodings in ASP.

Quantum algorithm for finding the negative curvature direction in non-convex optimization

no code implementations17 Sep 2019 Kaining Zhang, Min-Hsiu Hsieh, Liu Liu, DaCheng Tao

Moreover, we propose an efficient quantum algorithm to achieve the classical read-out of the target state.

NODE: Extreme Low Light Raw Image Denoising using a Noise Decomposition Network

no code implementations11 Sep 2019 Hao Guan, Liu Liu, Sean Moran, Fenglong Song, Gregory Slabaugh

In this paper, we propose a multi-task deep neural network called Noise Decomposition (NODE) that explicitly and separately estimates defective pixel noise, in conjunction with Gaussian and Poisson noise, to denoise an extreme low light image.

Image Denoising

Image Harmonization Dataset iHarmony4: HCOCO, HAdobe5k, HFlickr, and Hday2night

1 code implementation28 Aug 2019 Wenyan Cong, Jianfu Zhang, Li Niu, Liu Liu, Zhixin Ling, Weiyuan Li, Liqing Zhang

Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image.

Optimal Feature Transport for Cross-View Image Geo-Localization

1 code implementation11 Jul 2019 Yujiao Shi, Xin Yu, Liu Liu, Tong Zhang, Hongdong Li

This paper proposes a novel Cross-View Feature Transport (CVFT) technique to explicitly establish cross-view domain transfer that facilitates feature alignment between ground and aerial images.

Image-Based Localization Metric Learning

Lending Orientation to Neural Networks for Cross-view Geo-localization

1 code implementation CVPR 2019 Liu Liu, Hongdong Li

The goal is to predict the spatial location of a ground-level query image by matching it to a large geotagged aerial image database (e. g., satellite imagery).

FurcaNeXt: End-to-end monaural speech separation with dynamic gated dilated temporal convolutional networks

no code implementations12 Feb 2019 Ziqiang Shi, Huibin Lin, Liu Liu, Rujie Liu, Jiqing Han, Anyan Shi

Deep dilated temporal convolutional networks (TCN) have been proved to be very effective in sequence modeling.

Sound Audio and Speech Processing

High Dimensional Robust $M$-Estimation: Arbitrary Corruption and Heavy Tails

no code implementations24 Jan 2019 Liu Liu, Tianyang Li, Constantine Caramanis

We define a natural condition we call the Robust Descent Condition (RDC), and show that if a gradient estimator satisfies the RDC, then Robust Hard Thresholding (IHT using this gradient estimator), is guaranteed to obtain good statistical rates.

Dynamic Sparse Graph for Efficient Deep Learning

no code implementations ICLR 2019 Liu Liu, Lei Deng, Xing Hu, Maohua Zhu, Guoqi Li, Yufei Ding, Yuan Xie

We propose to execute deep neural networks (DNNs) with dynamic and sparse graph (DSG) structure for compressive memory and accelerative execution during both training and inference.

Dimensionality Reduction

Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient

no code implementations26 Sep 2018 Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, DaCheng Tao

Trust region and cubic regularization methods have demonstrated good performance in small scale non-convex optimization, showing the ability to escape from saddle points.

Stochastically Controlled Stochastic Gradient for the Convex and Non-convex Composition problem

no code implementations6 Sep 2018 Liu Liu, Ji Liu, Cho-Jui Hsieh, DaCheng Tao

In this paper, we consider the convex and non-convex composition problem with the structure $\frac{1}{n}\sum\nolimits_{i = 1}^n {{F_i}( {G( x )} )}$, where $G( x )=\frac{1}{n}\sum\nolimits_{j = 1}^n {{G_j}( x )} $ is the inner function, and $F_i(\cdot)$ is the outer function.

Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization

4 code implementations ICCV 2019 Liu Liu, Hongdong Li, Yuchao Dai

This paper tackles the problem of large-scale image-based localization (IBL) where the spatial location of a query image is determined by finding out the most similar reference images in a large database.

Image-Based Localization Representation Learning

Stochastic Zeroth-order Optimization via Variance Reduction method

no code implementations30 May 2018 Liu Liu, Minhao Cheng, Cho-Jui Hsieh, DaCheng Tao

However, due to the variance in the search direction, the convergence rates and query complexities of existing methods suffer from a factor of $d$, where $d$ is the problem dimension.

High Dimensional Robust Sparse Regression

no code implementations29 May 2018 Liu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis

Our algorithm recovers the true sparse parameters with sub-linear sample complexity, in the presence of a constant fraction of arbitrary corruptions.

Approximate Newton-based statistical inference using only stochastic gradients

no code implementations23 May 2018 Tianyang Li, Anastasios Kyrillidis, Liu Liu, Constantine Caramanis

We present a novel statistical inference framework for convex empirical risk minimization, using approximate stochastic Newton steps.

Time Series Time Series Analysis

Discriminative Cross-View Binary Representation Learning

no code implementations4 Apr 2018 Liu Liu, Hairong Qi

Learning compact representation is vital and challenging for large scale multimedia data.

Image Retrieval Quantization +1

L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks

no code implementations27 Feb 2018 Shuang Wu, Guoqi Li, Lei Deng, Liu Liu, Yuan Xie, Luping Shi

Batch Normalization (BN) has been proven to be quite effective at accelerating and improving the training of deep neural networks (DNNs).

Quantization

Variance Reduced methods for Non-convex Composition Optimization

no code implementations13 Nov 2017 Liu Liu, Ji Liu, DaCheng Tao

In this paper, we apply the variance-reduced technique to derive two variance reduced algorithms that significantly improve the query complexity if the number of inner component functions is large.

Duality-free Methods for Stochastic Composition Optimization

no code implementations26 Oct 2017 Liu Liu, Ji Liu, DaCheng Tao

We consider the composition optimization with two expected-value functions in the form of $\frac{1}{n}\sum\nolimits_{i = 1}^n F_i(\frac{1}{m}\sum\nolimits_{j = 1}^m G_j(x))+R(x)$, { which formulates many important problems in statistical learning and machine learning such as solving Bellman equations in reinforcement learning and nonlinear embedding}.

Efficient Global 2D-3D Matching for Camera Localization in a Large-Scale 3D Map

no code implementations ICCV 2017 Liu Liu, Hongdong Li, Yuchao Dai

In this paper, we introduce a global method which harnesses global contextual information exhibited both within the query image and among all the 3D points in the map.

3D Feature Matching Camera Localization

Person Re-identification Using Visual Attention

no code implementations23 Jul 2017 Alireza Rahimpour, Liu Liu, Ali Taalimi, Yang song, Hairong Qi

Despite recent attempts for solving the person re-identification problem, it remains a challenging task since a person's appearance can vary significantly when large variations in view angle, human pose, and illumination are involved.

Person Re-Identification

Multi-View Task-Driven Recognition in Visual Sensor Networks

no code implementations30 May 2017 Ali Taalimi, Alireza Rahimpour, Liu Liu, Hairong Qi

Nowadays, distributed smart cameras are deployed for a wide set of tasks in several application scenarios, ranging from object recognition, image retrieval, and forensic applications.

Image Retrieval Multi-Task Learning +3

Addressing Ambiguity in Multi-target Tracking by Hierarchical Strategy

no code implementations30 May 2017 Ali Taalimi, Liu Liu, Hairong Qi

We use a network flow approach to link detections in low-level and tracklets in high-level.

Statistical inference using SGD

no code implementations21 May 2017 Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis

We present a novel method for frequentist statistical inference in $M$-estimation problems, based on stochastic gradient descent (SGD) with a fixed step size: we demonstrate that the average of such SGD sequences can be used for statistical inference, after proper scaling.

Multi-view (Joint) Probability Linear Discrimination Analysis for Multi-view Feature Verification

no code implementations20 Apr 2017 Ziqiang Shi, Liu Liu, Mengjiao Wang, Rujie Liu

However, in practical use, when using multi-task learned network as feature extractor, the extracted feature are always attached to several labels.

Decision Making

End-to-end Binary Representation Learning via Direct Binary Embedding

no code implementations15 Mar 2017 Liu Liu, Alireza Rahimpour, Ali Taalimi, Hairong Qi

Furthermore, in the effort of handling multilabel images, we design a joint cross entropy loss that includes both softmax cross entropy and weighted binary cross entropy in consideration of the correlation and independence of labels, respectively.

Image Retrieval Object Recognition +2

CNNLab: a Novel Parallel Framework for Neural Networks using GPU and FPGA-a Practical Study with Trade-off Analysis

no code implementations20 Jun 2016 Maohua Zhu, Liu Liu, Chao Wang, Yuan Xie

To improve the performance and maintain the scalability, we present CNNLab, a novel deep learning framework using GPU and FPGA-based accelerators.

Robust and Efficient Relative Pose with a Multi-camera System for Autonomous Vehicle in Highly Dynamic Environments

no code implementations12 May 2016 Liu Liu, Hongdong Li, Yuchao Dai

When the solver is used in combination with RANSAC, we are able to quickly prune unpromising hypotheses, significantly improve the chance of finding inliers.

Motion Estimation

Compressing Deep Convolutional Networks using Vector Quantization

no code implementations18 Dec 2014 Yunchao Gong, Liu Liu, Ming Yang, Lubomir Bourdev

In this paper, we tackle this model storage issue by investigating information theoretical vector quantization methods for compressing the parameters of CNNs.

Classification General Classification +4

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