Search Results for author: Chen Liu

Found 79 papers, 32 papers with code

dS^2LBI: Exploring Structural Sparsity on Deep Network via Differential Inclusion Paths

no code implementations ICML 2020 Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO

Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.

Exploring Label Hierarchy in a Generative Way for Hierarchical Text Classification

no code implementations COLING 2022 Wei Huang, Chen Liu, Bo Xiao, Yihua Zhao, Zhaoming Pan, Zhimin Zhang, Xinyun Yang, Guiquan Liu

Hierarchical Text Classification (HTC), which aims to predict text labels organized in hierarchical space, is a significant task lacking in investigation in natural language processing.

text-classification Text Classification

Towards Mitigating Architecture Overfitting in Dataset Distillation

no code implementations8 Sep 2023 Xuyang Zhong, Chen Liu

Dataset distillation methods have demonstrated remarkable performance for neural networks trained with very limited training data.

Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning

no code implementations5 Sep 2023 Yong Lin, Chen Liu, Chenlu Ye, Qing Lian, Yuan YAO, Tong Zhang

Our proposed method, COPS (unCertainty based OPtimal Sub-sampling), is designed to minimize the expected loss of a model trained on subsampled data.

Active Learning

DeepVol: A Deep Transfer Learning Approach for Universal Asset Volatility Modeling

no code implementations5 Sep 2023 Chen Liu, Minh-Ngoc Tran, Chao Wang, Richard Gerlach, Robert Kohn

This paper introduces DeepVol, a promising new deep learning volatility model that outperforms traditional econometric models in terms of model generality.

Econometrics Transfer Learning

When 3D Bounding-Box Meets SAM: Point Cloud Instance Segmentation with Weak-and-Noisy Supervision

no code implementations2 Sep 2023 Qingtao Yu, Heming Du, Chen Liu, Xin Yu

CIP-WPIS leverages pretrained knowledge embedded in the 2D foundation model SAM and 3D geometric prior to achieve accurate point-wise instance labels from the bounding box annotations.

Instance Segmentation Semantic Segmentation

Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification

no code implementations24 Aug 2023 Ziqi Yang, Zhongyu Li, Chen Liu, Xiangde Luo, Xingguang Wang, Dou Xu, CHAOQUN LI, Xiaoying Qin, Meng Yang, Long Jin

To make full use of pixel-level and cell-level features dynamically, we propose an asymmetric co-training framework combining a deep graph convolutional network and a convolutional neural network for multi-class histopathological image classification.

Classification Histopathological Image Classification +1

BAVS: Bootstrapping Audio-Visual Segmentation by Integrating Foundation Knowledge

no code implementations20 Aug 2023 Chen Liu, Peike Li, Hu Zhang, Lincheng Li, Zi Huang, Dadong Wang, Xin Yu

In a nutshell, our BAVS is designed to eliminate the interference of background noise or off-screen sounds in segmentation by establishing the audio-visual correspondences in an explicit manner.

Audio Classification

Audio-Visual Segmentation by Exploring Cross-Modal Mutual Semantics

no code implementations31 Jul 2023 Chen Liu, Peike Li, Xingqun Qi, Hu Zhang, Lincheng Li, Dadong Wang, Xin Yu

However, we observed that prior arts are prone to segment a certain salient object in a video regardless of the audio information.

Semantic Segmentation

EmotionGesture: Audio-Driven Diverse Emotional Co-Speech 3D Gesture Generation

no code implementations30 May 2023 Xingqun Qi, Chen Liu, Lincheng Li, Jie Hou, Haoran Xin, Xin Yu

In this work, we propose EmotionGesture, a novel framework for synthesizing vivid and diverse emotional co-speech 3D gestures from audio.

Gesture Generation

RFAConv: Innovating Spatial Attention and Standard Convolutional Operation

1 code implementation6 Apr 2023 Xin Zhang, Chen Liu, Degang Yang, Tingting Song, Yichen Ye, Ke Li, Yingze Song

In this paper, we propose a new perspective on the effectiveness of spatial attention, which is that the spatial attention mechanism essentially solves the problem of convolutional kernel parameter sharing.

Classification Object Detection +1

Lung Nodule Segmentation and Uncertain Region Prediction with an Uncertainty-Aware Attention Mechanism

no code implementations15 Mar 2023 Han Yang, Qiuli Wang, Yue Zhang, Zhulin An, Chen Liu, Xiaohong Zhang, S. Kevin Zhou

Radiologists possess diverse training and clinical experiences, leading to variations in the segmentation annotations of lung nodules and resulting in segmentation uncertainty. Conventional methods typically select a single annotation as the learning target or attempt to learn a latent space comprising multiple annotations.

Lung Nodule Segmentation

Diverse 3D Hand Gesture Prediction from Body Dynamics by Bilateral Hand Disentanglement

1 code implementation CVPR 2023 Xingqun Qi, Chen Liu, Muyi Sun, Lincheng Li, Changjie Fan, Xin Yu

Considering the asymmetric gestures and motions of two hands, we introduce a Spatial-Residual Memory (SRM) module to model spatial interaction between the body and each hand by residual learning.


Realized recurrent conditional heteroskedasticity model for volatility modelling

1 code implementation16 Feb 2023 Chen Liu, Chao Wang, Minh-Ngoc Tran, Robert Kohn

We propose a new approach to volatility modelling by combining deep learning (LSTM) and realized volatility measures.

Bayesian Inference Econometrics

Leveraging Diffusion For Strong and High Quality Face Morphing Attacks

no code implementations10 Jan 2023 Zander Blasingame, Chen Liu

Face morphing attacks seek to deceive a Face Recognition (FR) system by presenting a morphed image consisting of the biometric qualities from two different identities with the aim of triggering a false acceptance with one of the two identities, thereby presenting a significant threat to biometric systems.

Face Recognition Vocal Bursts Intensity Prediction

Split-PU: Hardness-aware Training Strategy for Positive-Unlabeled Learning

1 code implementation30 Nov 2022 Chengming Xu, Chen Liu, Siqian Yang, Yabiao Wang, Shijie Zhang, Lijie Jia, Yanwei Fu

Since only part of the most confident positive samples are available and evidence is not enough to categorize the rest samples, many of these unlabeled data may also be the positive samples.

Binary Classification

PatchMix Augmentation to Identify Causal Features in Few-shot Learning

no code implementations29 Nov 2022 Chengming Xu, Chen Liu, Xinwei Sun, Siqian Yang, Yabiao Wang, Chengjie Wang, Yanwei Fu

We theoretically show that such an augmentation mechanism, different from existing ones, is able to identify the causal features.

Data Augmentation Few-Shot Learning +1

Uncertainty-aware Gait Recognition via Learning from Dirichlet Distribution-based Evidence

no code implementations15 Nov 2022 Beibei Lin, Chen Liu, Lincheng Li, Robby T. Tan, Xin Yu

Existing gait recognition frameworks retrieve an identity in the gallery based on the distance between a probe sample and the identities in the gallery.

Gait Recognition Retrieval

Behavior Prior Representation learning for Offline Reinforcement Learning

1 code implementation2 Nov 2022 Hongyu Zang, Xin Li, Jie Yu, Chen Liu, Riashat Islam, Remi Tachet des Combes, Romain Laroche

Our method, Behavior Prior Representation (BPR), learns state representations with an easy-to-integrate objective based on behavior cloning of the dataset: we first learn a state representation by mimicking actions from the dataset, and then train a policy on top of the fixed representation, using any off-the-shelf Offline RL algorithm.

Offline RL reinforcement-learning +2

Learning to Learn and Sample BRDFs

1 code implementation7 Oct 2022 Chen Liu, Michael Fischer, Tobias Ritschel

We propose a method to accelerate the joint process of physically acquiring and learning neural Bi-directional Reflectance Distribution Function (BRDF) models.


CUTS: A Fully Unsupervised Framework for Medical Image Segmentation

1 code implementation23 Sep 2022 Chen Liu, Matthew Amodio, Liangbo L. Shen, Feng Gao, Arman Avesta, Sanjay Aneja, Jay C. Wang, Lucian V. Del Priore, Smita Krishnaswamy

In this work we introduce CUTS (Contrastive and Unsupervised Training for Segmentation), a fully unsupervised deep learning framework for medical image segmentation to better utilize the vast majority of imaging data that is not labeled or annotated.

Contrastive Learning Image Segmentation +3

$\textbf{P$^2$A}$: A Dataset and Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos

no code implementations26 Jul 2022 Jiang Bian, Qingzhong Wang, Haoyi Xiong, Jun Huang, Chen Liu, Xuhong LI, Jun Cheng, Jun Zhao, Feixiang Lu, Dejing Dou

While deep learning has been widely used for video analytics, such as video classification and action detection, dense action detection with fast-moving subjects from sports videos is still challenging.

Action Detection Action Localization +2

Adversarial Focal Loss: Asking Your Discriminator for Hard Examples

no code implementations15 Jul 2022 Chen Liu, Xiaomeng Dong, Michael Potter, Hsi-Ming Chang, Ravi Soni

In this paper, we propose a novel adaptation of Focal Loss for keypoint detection tasks, called Adversarial Focal Loss (AFL).

Keypoint Detection

Dual Windows Are Significant: Learning from Mediastinal Window and Focusing on Lung Window

no code implementations8 Jun 2022 Qiuli Wang, Xin Tan, Chen Liu

Since the pandemic of COVID-19, several deep learning methods were proposed to analyze the chest Computed Tomography (CT) for diagnosis.

Computed Tomography (CT)

Fast Adversarial Training with Adaptive Step Size

no code implementations6 Jun 2022 Zhichao Huang, Yanbo Fan, Chen Liu, Weizhong Zhang, Yong Zhang, Mathieu Salzmann, Sabine Süsstrunk, Jue Wang

While adversarial training and its variants have shown to be the most effective algorithms to defend against adversarial attacks, their extremely slow training process makes it hard to scale to large datasets like ImageNet.

Neural Inertial Localization

1 code implementation CVPR 2022 Sachini Herath, David Caruso, Chen Liu, Yufan Chen, Yasutaka Furukawa

This paper proposes the inertial localization problem, the task of estimating the absolute location from a sequence of inertial sensor measurements.

Indoor Localization Privacy Preserving

Delving Deeper into Cross-lingual Visual Question Answering

1 code implementation15 Feb 2022 Chen Liu, Jonas Pfeiffer, Anna Korhonen, Ivan Vulić, Iryna Gurevych

2) We analyze cross-lingual VQA across different question types of varying complexity for different multilingual multimodal Transformers, and identify question types that are the most difficult to improve on.

Inductive Bias Question Answering +1

Robust Binary Models by Pruning Randomly-initialized Networks

1 code implementation3 Feb 2022 Chen Liu, Ziqi Zhao, Sabine Süsstrunk, Mathieu Salzmann

In this paper, we introduce an approach to obtain robust yet compact models by pruning randomly-initialized binary networks.

On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training

no code implementations14 Dec 2021 Chen Liu, Zhichao Huang, Mathieu Salzmann, Tong Zhang, Sabine Süsstrunk

This lets us show that the decay in generalization performance of adversarial training is a result of the model's attempt to fit hard adversarial instances.

Improving Adversarial Defense with Self-supervised Test-time Fine-tuning

no code implementations29 Sep 2021 Zhichao Huang, Chen Liu, Mathieu Salzmann, Sabine Süsstrunk, Tong Zhang

Although adversarial training and its variants currently constitute the most effective way to achieve robustness against adversarial attacks, their poor generalization limits their performance on the test samples.

Adversarial Defense

Hierarchy-Aware T5 with Path-Adaptive Mask Mechanism for Hierarchical Text Classification

no code implementations17 Sep 2021 Wei Huang, Chen Liu, Yihua Zhao, Xinyun Yang, Zhaoming Pan, Zhimin Zhang, Guiquan Liu

Hierarchical Text Classification (HTC), which aims to predict text labels organized in hierarchical space, is a significant task lacking in investigation in natural language processing.

text-classification Text Classification

FLiText: A Faster and Lighter Semi-Supervised Text Classification with Convolution Networks

1 code implementation EMNLP 2021 Chen Liu, Mengchao Zhang, Zhibin Fu, Pan Hou, Yu Li

In natural language processing (NLP), state-of-the-art (SOTA) semi-supervised learning (SSL) frameworks have shown great performance on deep pre-trained language models such as BERT, and are expected to significantly reduce the demand for manual labeling.

Semi-Supervised Text Classification

Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation

no code implementations8 Sep 2021 Geng-Xin Xu, Chen Liu, Jun Liu, Zhongxiang Ding, Feng Shi, Man Guo, Wei Zhao, Xiaoming Li, Ying WEI, Yaozong Gao, Chuan-Xian Ren, Dinggang Shen

Particularly, we propose a domain translator and align the heterogeneous data to the estimated class prototypes (i. e., class centers) in a hyper-sphere manifold.

Computed Tomography (CT) Domain Adaptation +1

Multi-objective Scheduling of Electric Vehicle Charging/Discharging with Time of Use Tariff

no code implementations11 Aug 2021 Hui Song, Chen Liu, Mahdi Jalili, Xinghuo Yu, Peter McTaggart

Optimal coordinated charging is a multi-objective optimization problem (MOOP) in nature, with objective functions such as minimum price charging and minimum disruptions to the grid.


MG-DVD: A Real-time Framework for Malware Variant Detection Based on Dynamic Heterogeneous Graph Learning

no code implementations23 Jun 2021 Chen Liu, Bo Li, Jun Zhao, Ming Su, Xu-Dong Liu

In this paper, we propose MG-DVD, a novel detection framework based on dynamic heterogeneous graph learning, to detect malware variants in real time.

Blocking Graph Learning

Fourier Transform Approximation as an Auxiliary Task for Image Classification

1 code implementation22 Jun 2021 Chen Liu

Image reconstruction is likely the most predominant auxiliary task for image classification, but we would like to think twice about this convention.

Classification Image Classification +1

An Architecture for Accelerated Large-Scale Inference of Transformer-Based Language Models

no code implementations NAACL 2021 Amir Ganiev, Colton Chapin, Anderson de Andrade, Chen Liu

We used a BERT model that was fine-tuned for emotion analysis, returning a probability distribution of emotions given a paragraph.

Emotion Recognition

Deep Learning Identifies Neuroimaging Signatures of Alzheimer's Disease Using Structural and Synthesized Functional MRI Data

no code implementations10 Apr 2021 Nanyan Zhu, Chen Liu, Xinyang Feng, Dipika Sikka, Sabrina Gjerswold-Selleck, Scott A. Small, Jia Guo

Here we propose a potential solution by first learning a structural-to-functional transformation in brain MRI, and further synthesizing spatially matched functional images from large-scale structural scans.

Learning Dynamic Alignment via Meta-filter for Few-shot Learning

1 code implementation CVPR 2021 Chengming Xu, Chen Liu, Li Zhang, Chengjie Wang, Jilin Li, Feiyue Huang, xiangyang xue, Yanwei Fu

Our insight is that these methods would lead to poor adaptation with redundant matching, and leveraging channel-wise adjustment is the key to well adapting the learned knowledge to new classes.

Few-Shot Learning

Example-based Real-time Clothing Synthesis for Virtual Agents

no code implementations8 Jan 2021 Nannan Wu, Qianwen Chao, Yanzhen Chen, Weiwei Xu, Chen Liu, Dinesh Manocha, Wenxin Sun, Yi Han, Xinran Yao, Xiaogang Jin

Given a query shape and pose of the virtual agent, we synthesize the resulting clothing deformation by blending the Taylor expansion results of nearby anchoring points.


Beyond COVID-19 Diagnosis: Prognosis with Hierarchical Graph Representation Learning

no code implementations1 Jan 2021 Chen Liu, Jinze Cui, Dailin Gan, Guosheng Yin

Our method, combining GCNs and distance aware pooling, can integrate the information from all slices in the chest CT scans for optimal decision making, which leads to the state-of-the-art accuracy in the COVID-19 diagnosis and prognosis.

Computed Tomography (CT) COVID-19 Diagnosis +2

Revealing the origins of shear band activity and boundary strengthening in polygrain-like architected materials

no code implementations4 Nov 2020 Chen Liu, Jedsada Lertthanasarn, Minh-Son Pham

A recent report on successful employment of the grain boundary strengthening to design extraordinarily damage-tolerant architected materials (i. e. meta-crystals) necessitates fundamental studies to understand the underlying mechanisms responsible for the toughening and high performance of meta-crystals.

Materials Science

Efficient Unpaired Image Dehazing with Cyclic Perceptual-Depth Supervision

no code implementations10 Jul 2020 Chen Liu, Jiaqi Fan, Guosheng Yin

Image dehazing without paired haze-free images is of immense importance, as acquiring paired images often entails significant cost.

Image Dehazing

DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths

1 code implementation4 Jul 2020 Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO

Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.

Graph Representation Learning Network via Adaptive Sampling

1 code implementation8 Jun 2020 Anderson de Andrade, Chen Liu

Graph Attention Network (GAT) and GraphSAGE are neural network architectures that operate on graph-structured data and have been widely studied for link prediction and node classification.

Graph Attention Graph Representation Learning +2

Jointly Encoding Word Confusion Network and Dialogue Context with BERT for Spoken Language Understanding

1 code implementation24 May 2020 Chen Liu, Su Zhu, Zijian Zhao, Ruisheng Cao, Lu Chen, Kai Yu

In this paper, a novel BERT based SLU model (WCN-BERT SLU) is proposed to encode WCNs and the dialogue context jointly.

Spoken Language Understanding

Instance Credibility Inference for Few-Shot Learning

1 code implementation CVPR 2020 Yikai Wang, Chengming Xu, Chen Liu, Li Zhang, Yanwei Fu

To measure the credibility of each pseudo-labeled instance, we then propose to solve another linear regression hypothesis by increasing the sparsity of the incidental parameters and rank the pseudo-labeled instances with their sparsity degree.

Data Augmentation Few-Shot Image Classification +2

Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features

1 code implementation15 Jan 2020 Nanyan Zhu, Chen Liu, Zakary S. Singer, Tal Danino, Andrew F. Laine, Jia Guo

The ability to extrapolate gene expression dynamics in living single cells requires robust cell segmentation, and one of the challenges is the amorphous or irregularly shaped cell boundaries.

Cell Segmentation Specificity

Training Provably Robust Models by Polyhedral Envelope Regularization

1 code implementation10 Dec 2019 Chen Liu, Mathieu Salzmann, Sabine Süsstrunk

Training certifiable neural networks enables one to obtain models with robustness guarantees against adversarial attacks.

DENS: A Dataset for Multi-class Emotion Analysis

no code implementations IJCNLP 2019 Chen Liu, Muhammad Osama, Anderson de Andrade

Our results show that the dataset provides a novel opportunity in emotion analysis that requires moving beyond existing sentence-level techniques.

Emotion Recognition

Boosting Network: Learn by Growing Filters and Layers via SplitLBI

no code implementations25 Sep 2019 Zuyuan Zhong, Chen Liu, Yanwei Fu, Yuan YAO

Network structures are important to learning good representations of many tasks in computer vision and machine learning communities.

Neural Architecture Search

Split LBI for Deep Learning: Structural Sparsity via Differential Inclusion Paths

no code implementations25 Sep 2019 Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO

Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.

Floor-SP: Inverse CAD for Floorplans by Sequential Room-wise Shortest Path

1 code implementation ICCV 2019 Jiacheng Chen, Chen Liu, Jiaye Wu, Yasutaka Furukawa

This paper proposes a new approach for automated floorplan reconstruction from RGBD scans, a major milestone in indoor mapping research.

Edge Detection

Coherent and Controllable Outfit Generation

no code implementations17 Jun 2019 Kedan Li, Chen Liu, David Forsyth

A user study suggests that people understand the match between the queries and the outfits produced by our method.

General Classification

Exploring Structural Sparsity of Deep Networks via Inverse Scale Spaces

1 code implementation23 May 2019 Yanwei Fu, Chen Liu, Donghao Li, Zuyuan Zhong, Xinwei Sun, Jinshan Zeng, Yuan YAO

To fill in this gap, this paper proposes a new approach based on differential inclusions of inverse scale spaces, which generate a family of models from simple to complex ones along the dynamics via coupling a pair of parameters, such that over-parameterized deep models and their structural sparsity can be explored simultaneously.

On Certifying Non-uniform Bound against Adversarial Attacks

no code implementations15 Mar 2019 Chen Liu, Ryota Tomioka, Volkan Cevher

This work studies the robustness certification problem of neural network models, which aims to find certified adversary-free regions as large as possible around data points.

MASC: Multi-scale Affinity with Sparse Convolution for 3D Instance Segmentation

1 code implementation12 Feb 2019 Chen Liu, Yasutaka Furukawa

We propose a new approach for 3D instance segmentation based on sparse convolution and point affinity prediction, which indicates the likelihood of two points belonging to the same instance.

3D Instance Segmentation Clustering +1

Deep Heterogeneous Autoencoders for Collaborative Filtering

no code implementations17 Dec 2018 Tianyu Li, Yukun Ma, Jiu Xu, Bjorn Stenger, Chen Liu, Yu Hirate

This paper leverages heterogeneous auxiliary information to address the data sparsity problem of recommender systems.

Collaborative Filtering Recommendation Systems

PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image

2 code implementations CVPR 2019 Chen Liu, Kihwan Kim, Jinwei Gu, Yasutaka Furukawa, Jan Kautz

This paper proposes a deep neural architecture, PlaneRCNN, that detects and reconstructs piecewise planar surfaces from a single RGB image.

3D Plane Detection 3D Reconstruction

Finding Mixed Nash Equilibria of Generative Adversarial Networks

no code implementations ICLR 2019 Ya-Ping Hsieh, Chen Liu, Volkan Cevher

We reconsider the training objective of Generative Adversarial Networks (GANs) from the mixed Nash Equilibria (NE) perspective.

PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image

1 code implementation CVPR 2018 Chen Liu, Jimei Yang, Duygu Ceylan, Ersin Yumer, Yasutaka Furukawa

The proposed end-to-end DNN learns to directly infer a set of plane parameters and corresponding plane segmentation masks from a single RGB image.

Depth Estimation Depth Prediction

FloorNet: A Unified Framework for Floorplan Reconstruction from 3D Scans

2 code implementations ECCV 2018 Chen Liu, Jiaye Wu, Yasutaka Furukawa

The ultimate goal of this indoor mapping research is to automatically reconstruct a floorplan simply by walking through a house with a smartphone in a pocket.

Vector Graphics

Teaching Autonomous Driving Using a Modular and Integrated Approach

no code implementations22 Feb 2018 Jie Tang, Shaoshan Liu, Songwen Pei, Stephane Zuckerman, Chen Liu, Weisong Shi, Jean-Luc Gaudiot

Then, once the students have understood these modules, the experimental platforms for integration we have developed allow the students to fully understand how the modules interact with each other.

Autonomous Driving

Raster-To-Vector: Revisiting Floorplan Transformation

1 code implementation ICCV 2017 Chen Liu, Jiajun Wu, Pushmeet Kohli, Yasutaka Furukawa

A neural architecture first transforms a rasterized image to a set of junctions that represent low-level geometric and semantic information (e. g., wall corners or door end-points).

Vector Graphics

Deep Multi-Modal Image Correspondence Learning

no code implementations5 Dec 2016 Chen Liu, Jiajun Wu, Pushmeet Kohli, Yasutaka Furukawa

Our result implies that neural networks are effective at perceptual tasks that require long periods of reasoning even for humans to solve.

Multi-way Particle Swarm Fusion

no code implementations5 Dec 2016 Chen Liu, Hang Yan, Pushmeet Kohli, Yasutaka Furukawa

This paper proposes a novel MAP inference framework for Markov Random Field (MRF) in parallel computing environments.

Optical Flow Estimation

Layered Scene Decomposition via the Occlusion-CRF

no code implementations CVPR 2016 Chen Liu, Pushmeet Kohli, Yasutaka Furukawa

This paper addresses the challenging problem of perceiving the hidden or occluded geometry of the scene depicted in any given RGBD image.

Image Segmentation Semantic Segmentation

Driving rate dependence of avalanche statistics and shapes at the yielding transition

1 code implementation26 Jun 2015 Chen Liu, Ezequiel E. Ferrero, Francesco Puosi, Jean-Louis Barrat, Kirsten Martens

We study stress time series caused by plastic avalanches in athermally sheared disordered materials.

Soft Condensed Matter Statistical Mechanics

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