Search Results for author: Chen Gao

Found 76 papers, 43 papers with code

Modeling User Fatigue for Sequential Recommendation

1 code implementation20 May 2024 Nian Li, Xin Ban, Cheng Ling, Chen Gao, Lantao Hu, Peng Jiang, Kun Gai, Yong Li, Qingmin Liao

In this paper, we propose to model user Fatigue in interest learning for sequential Recommendations (FRec).

Contrastive Learning Sequential Recommendation

Depression Detection on Social Media with Large Language Models

no code implementations16 Mar 2024 Xiaochong Lan, Yiming Cheng, Li Sheng, Chen Gao, Yong Li

Depression detection aims to determine whether an individual suffers from depression by analyzing their history of posts on social media, which can significantly aid in early detection and intervention.

Benchmarking Depression Detection

Eliminating Cross-modal Conflicts in BEV Space for LiDAR-Camera 3D Object Detection

no code implementations12 Mar 2024 Jiahui Fu, Chen Gao, Zitian Wang, Lirong Yang, Xiaofei Wang, Beipeng Mu, Si Liu

Recent 3D object detectors typically utilize multi-sensor data and unify multi-modal features in the shared bird's-eye view (BEV) representation space.

3D Object Detection object-detection

Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendation

no code implementations7 Mar 2024 Nicholas Sukiennik, Chen Gao, Nian Li

We formalize our definition of a "deep" filter bubble within this context, and then explore various correlations within the data: first understanding the evolution of the deep filter bubble over time, and later revealing some of the factors that give rise to this phenomenon, such as specific categories, user demographics, and feedback type.

Recommendation Systems

Identify Critical Nodes in Complex Network with Large Language Models

no code implementations1 Mar 2024 Jinzhu Mao, Dongyun Zou, Li Sheng, Siyi Liu, Chen Gao, Yue Wang, Yong Li

Identifying critical nodes in networks is a classical decision-making task, and many methods struggle to strike a balance between adaptability and utility.

Decision Making

LLM4SBR: A Lightweight and Effective Framework for Integrating Large Language Models in Session-based Recommendation

no code implementations21 Feb 2024 Shutong Qiao, Chen Gao, Junhao Wen, Wei Zhou, Qun Luo, Peixuan Chen, Yong Li

However, constrained by high time and space costs, as well as the brief and anonymous nature of session data, the first LLM recommendation framework suitable for industrial deployment has yet to emerge in the field of SBR.

Session-Based Recommendations

Improving Cognitive Diagnosis Models with Adaptive Relational Graph Neural Networks

no code implementations15 Feb 2024 Pengyang Shao, Chen Gao, Lei Chen, Yonghui Yang, Kun Zhang, Meng Wang

Typically, these CD algorithms assist students by inferring their abilities (i. e., their proficiency levels on various knowledge concepts).

cognitive diagnosis

Large Language Model Agent for Hyper-Parameter Optimization

no code implementations2 Feb 2024 Siyi Liu, Chen Gao, Yong Li

Hyperparameter optimization is critical in modern machine learning, requiring expert knowledge, numerous trials, and high computational and human resources.

Hyperparameter Optimization Language Modelling +1

SpecNeRF: Gaussian Directional Encoding for Specular Reflections

no code implementations20 Dec 2023 Li Ma, Vasu Agrawal, Haithem Turki, Changil Kim, Chen Gao, Pedro Sander, Michael Zollhöfer, Christian Richardt

We show that our Gaussian directional encoding and geometry prior significantly improve the modeling of challenging specular reflections in neural radiance fields, which helps decompose appearance into more physically meaningful components.

Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment

1 code implementation19 Dec 2023 Fengli Xu, Jun Zhang, Chen Gao, Jie Feng, Yong Li

Urban environments, characterized by their complex, multi-layered networks encompassing physical, social, economic, and environmental dimensions, face significant challenges in the face of rapid urbanization.

Mixed Attention Network for Cross-domain Sequential Recommendation

1 code implementation14 Nov 2023 GuanYu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang

Recent proposed cross-domain sequential recommendation models such as PiNet and DASL have a common drawback relying heavily on overlapped users in different domains, which limits their usage in practical recommender systems.

Sequential Recommendation

Inverse Learning with Extremely Sparse Feedback for Recommendation

1 code implementation14 Nov 2023 GuanYu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li

In this paper, we propose a meta-learning method to annotate the unlabeled data from loss and gradient perspectives, which considers the noises in both positive and negative instances.


Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

no code implementations10 Nov 2023 Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang

Prior attempts have quantified the privacy risks of language models (LMs) via MIAs, but there is still no consensus on whether existing MIA algorithms can cause remarkable privacy leakage on practical Large Language Models (LLMs).

Inference Attack Membership Inference Attack +1

Stance Detection with Collaborative Role-Infused LLM-Based Agents

1 code implementation16 Oct 2023 Xiaochong Lan, Chen Gao, Depeng Jin, Yong Li

Next, in the reasoning-enhanced debating stage, for each potential stance, we designate a specific LLM-based agent to advocate for it, guiding the LLM to detect logical connections between text features and stance, tackling the second challenge.

CoLA Stance Detection

EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities

1 code implementation16 Oct 2023 Nian Li, Chen Gao, Mingyu Li, Yong Li, Qingmin Liao

Existing agent modeling typically employs predetermined rules or learning-based neural networks for decision-making.

Decision Making Language Modelling +2

OmnimatteRF: Robust Omnimatte with 3D Background Modeling

1 code implementation ICCV 2023 Geng Lin, Chen Gao, Jia-Bin Huang, Changil Kim, Yipeng Wang, Matthias Zwicker, Ayush Saraf

Video matting has broad applications, from adding interesting effects to casually captured movies to assisting video production professionals.

Image Matting Video Matting

Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception

no code implementations31 Aug 2023 Si Liu, Chen Gao, Yuan Chen, Xingyu Peng, Xianghao Kong, Kun Wang, Runsheng Xu, Wentao Jiang, Hao Xiang, Jiaqi Ma, Miao Wang

Specifically, we analyze the performance changes of different methods under different bandwidths, providing a deep insight into the performance-bandwidth trade-off issue.

Autonomous Driving

Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System

no code implementations25 Aug 2023 Yunzhu Pan, Nian Li, Chen Gao, Jianxin Chang, Yanan Niu, Yang song, Depeng Jin, Yong Li

Specifically, in short-video recommendation, the easiest-to-collect user feedback is the skipping behavior, which leads to two critical challenges for the recommendation model.

Recommendation Systems

A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Models

no code implementations23 Aug 2023 Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang

Membership Inference Attack (MIA) identifies whether a record exists in a machine learning model's training set by querying the model.

Inference Attack Membership Inference Attack +1

Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation

no code implementations8 Aug 2023 Yunzhu Pan, Chen Gao, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Depeng Jin, Yong Li

To enhance the robustness of our model, we then introduce a multi-task learning module to simultaneously optimize two kinds of feedback -- passive-negative feedback and traditional randomly-sampled negative feedback.

Multi-Task Learning Sequential Recommendation

Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation

no code implementations7 Aug 2023 Taichi Liu, Chen Gao, Zhenyu Wang, Dong Li, Jianye Hao, Depeng Jin, Yong Li

Graph Neural Network (GNN)-based models have become the mainstream approach for recommender systems.

Recommendation Systems

NEON: Living Needs Prediction System in Meituan

no code implementations31 Jul 2023 Xiaochong Lan, Chen Gao, Shiqi Wen, Xiuqi Chen, Yingge Che, Han Zhang, Huazhou Wei, Hengliang Luo, Yong Li

To address these two challenges, we design a system of living NEeds predictiON named NEON, consisting of three phases: feature mining, feature fusion, and multi-task prediction.

Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network

1 code implementation19 Jul 2023 Jinzhu Mao, Liu Cao, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, Yong Li

Understanding and characterizing the vulnerability of urban infrastructures, which refers to the engineering facilities essential for the regular running of cities and that exist naturally in the form of networks, is of great value to us.

Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering

1 code implementation12 Jul 2023 Yan Wen, Chen Gao, Lingling Yi, Liwei Qiu, Yaqing Wang, Yong Li

Automated Machine Learning (AutoML) techniques have recently been introduced to design Collaborative Filtering (CF) models in a data-specific manner.

AutoML Collaborative Filtering

Robust Preference-Guided Denoising for Graph based Social Recommendation

1 code implementation15 Mar 2023 Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin, Yong Li

Graph Neural Network(GNN) based social recommendation models improve the prediction accuracy of user preference by leveraging GNN in exploiting preference similarity contained in social relations.

Denoising Relation

Dual-interest Factorization-heads Attention for Sequential Recommendation

1 code implementation8 Feb 2023 GuanYu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang song, Zhiheng Li, Depeng Jin, Yong Li

In this paper, we propose Dual-interest Factorization-heads Attention for Sequential Recommendation (short for DFAR) consisting of feedback-aware encoding layer, dual-interest disentangling layer and prediction layer.

Disentanglement Sequential Recommendation

Robust Dynamic Radiance Fields

1 code implementation CVPR 2023 Yu-Lun Liu, Chen Gao, Andreas Meuleman, Hung-Yu Tseng, Ayush Saraf, Changil Kim, Yung-Yu Chuang, Johannes Kopf, Jia-Bin Huang

Dynamic radiance field reconstruction methods aim to model the time-varying structure and appearance of a dynamic scene.

Adaptive Zone-Aware Hierarchical Planner for Vision-Language Navigation

1 code implementation CVPR 2023 Chen Gao, Xingyu Peng, Mi Yan, He Wang, Lirong Yang, Haibing Ren, Hongsheng Li, Si Liu

In this paper, we propose an Adaptive Zone-aware Hierarchical Planner (AZHP) to explicitly divides the navigation process into two heterogeneous phases, i. e., sub-goal setting via zone partition/selection (high-level action) and sub-goal executing (low-level action), for hierarchical planning.

Vision-Language Navigation

Mutual Harmony: Sequential Recommendation with Dual Contrastive Network

1 code implementation18 Sep 2022 GuanYu Lin, Chen Gao, Yinfeng Li, Yu Zheng, Zhiheng Li, Depeng Jin, Dong Li, Jianye Hao, Yong Li

Such user-centric recommendation will make it impossible for the provider to expose their new items, failing to consider the accordant interactions between user and item dimensions.

Contrastive Learning Representation Learning +1

Causal Inference in Recommender Systems: A Survey and Future Directions

1 code implementation26 Aug 2022 Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, Yong Li

Existing recommender systems extract user preferences based on the correlation in data, such as behavioral correlation in collaborative filtering, feature-feature, or feature-behavior correlation in click-through rate prediction.

Causal Inference Click-Through Rate Prediction +2

DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction

1 code implementation14 Aug 2022 Yinfeng Li, Chen Gao, Quanming Yao, Tong Li, Depeng Jin, Yong Li

In particular, we first unify the fine-grained user similarity and the complex matching between user preferences and spatiotemporal activity into a heterogeneous hypergraph.

Activity Prediction Graph Embedding +1

Practitioners Versus Users: A Value-Sensitive Evaluation of Current Industrial Recommender System Design

no code implementations8 Aug 2022 Zhilong Chen, Jinghua Piao, Xiaochong Lan, Hancheng Cao, Chen Gao, Zhicong Lu, Yong Li

Recommender systems are playing an increasingly important role in alleviating information overload and supporting users' various needs, e. g., consumption, socialization, and entertainment.

Fairness Recommendation Systems

Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation

no code implementations3 Aug 2022 Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang

More specifically, we propose a novel Coarse-to-fine Knowledge-enhanced Multi-interest Learning (CKML) framework to learn shared and behavior-specific interests for different behaviors.

Target-Driven Structured Transformer Planner for Vision-Language Navigation

1 code implementation19 Jul 2022 Yusheng Zhao, Jinyu Chen, Chen Gao, Wenguan Wang, Lirong Yang, Haibing Ren, Huaxia Xia, Si Liu

Vision-language navigation is the task of directing an embodied agent to navigate in 3D scenes with natural language instructions.

Navigate Vision-Language Navigation

Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation

1 code implementation26 May 2022 Mingshi Yan, Zhiyong Cheng, Chen Gao, Jing Sun, Fan Liu, Fuming Sun, Haojie Li

In particular, we design a cascading residual graph convolutional network structure, which enables our model to learn user preferences by continuously refining user embeddings across different types of behaviors.

Multi-Task Learning

Reinforced Structured State-Evolution for Vision-Language Navigation

1 code implementation CVPR 2022 Jinyu Chen, Chen Gao, Erli Meng, Qiong Zhang, Si Liu

However, the crucial navigation clues (i. e., object-level environment layout) for embodied navigation task is discarded since the maintained vector is essentially unstructured.

Navigate Vision and Language Navigation +1

3D-SPS: Single-Stage 3D Visual Grounding via Referred Point Progressive Selection

1 code implementation CVPR 2022 Junyu Luo, Jiahui Fu, Xianghao Kong, Chen Gao, Haibing Ren, Hao Shen, Huaxia Xia, Si Liu

3D visual grounding aims to locate the referred target object in 3D point cloud scenes according to a free-form language description.

Visual Grounding

Remaining Useful Life Prediction Using Temporal Deep Degradation Network for Complex Machinery with Attention-based Feature Extraction

no code implementations21 Feb 2022 Yuwen Qin, Ningbo Cai, Chen Gao, Yadong Zhang, Yonghong Cheng, Xin Chen

The degradation-related features extracted from the sensor streaming data with neural networks can dramatically improve the accuracy of the RUL prediction.

Progressive Feature Interaction Search for Deep Sparse Network

no code implementations NeurIPS 2021 Chen Gao, Yinfeng Li, Quanming Yao, Depeng Jin, Yong Li

Deep sparse networks (DSNs), of which the crux is exploring the high-order feature interactions, have become the state-of-the-art on the prediction task with high-sparsity features.

Neural Architecture Search

Session-aware Item-combination Recommendation with Transformer Network

1 code implementation13 Nov 2021 Tzu-Heng Lin, Chen Gao

In this paper, we detailedly describe our solution for the IEEE BigData Cup 2021: RL-based RecSys (Track 1: Item Combination Prediction).

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks

1 code implementation5 Nov 2021 Zirui Zhu, Chen Gao, Xu Chen, Nian Li, Depeng Jin, Yong Li

With the hypergraph convolutional networks, the social relations can be modeled in a more fine-grained manner, which more accurately depicts real users' preferences, and benefits the recommendation performance.

Improving Location Recommendation with Urban Knowledge Graph

no code implementations1 Nov 2021 Chang Liu, Chen Gao, Depeng Jin, Yong Li

We first conduct information propagation on two sub-graphs to learn the representations of POIs and users.


DGCN: Diversified Recommendation with Graph Convolutional Networks

2 code implementations16 Aug 2021 Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li

These years much effort has been devoted to improving the accuracy or relevance of the recommendation system.

Collaborative Filtering

Sequential Recommendation with Graph Neural Networks

1 code implementation27 Jun 2021 Jianxin Chang, Chen Gao, Yu Zheng, Yiqun Hui, Yanan Niu, Yang song, Depeng Jin, Yong Li

This helps explicitly distinguish users' core interests, by forming dense clusters in the interest graph.

Metric Learning Sequential Recommendation

Room-and-Object Aware Knowledge Reasoning for Remote Embodied Referring Expression

1 code implementation CVPR 2021 Chen Gao, Jinyu Chen, Si Liu, Luting Wang, Qiong Zhang, Qi Wu

The Remote Embodied Referring Expression (REVERIE) is a recently raised task that requires an agent to navigate to and localise a referred remote object according to a high-level language instruction.

Instruction Following Navigate +2

Efficient Data-specific Model Search for Collaborative Filtering

no code implementations14 Jun 2021 Chen Gao, Quanming Yao, Depeng Jin, Yong Li

In this way, we can combinatorially generalize data-specific CF models, which have not been visited in the literature, from SOTA ones.

AutoML Collaborative Filtering +1

PSGAN++: Robust Detail-Preserving Makeup Transfer and Removal

1 code implementation26 May 2021 Si Liu, Wentao Jiang, Chen Gao, Ran He, Jiashi Feng, Bo Li, Shuicheng Yan

In this paper, we address the makeup transfer and removal tasks simultaneously, which aim to transfer the makeup from a reference image to a source image and remove the makeup from the with-makeup image respectively.

Style Transfer

Dynamic View Synthesis from Dynamic Monocular Video

1 code implementation ICCV 2021 Chen Gao, Ayush Saraf, Johannes Kopf, Jia-Bin Huang

We present an algorithm for generating novel views at arbitrary viewpoints and any input time step given a monocular video of a dynamic scene.

Learnable Embedding Sizes for Recommender Systems

1 code implementation ICLR 2021 Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, Yong Li

Existing works that try to address the problem always cause a significant drop in recommendation performance or suffers from the limitation of unaffordable training time cost.

Recommendation Systems Representation Learning

Language-Guided Global Image Editing via Cross-Modal Cyclic Mechanism

no code implementations ICCV 2021 Wentao Jiang, Ning Xu, Jiayun Wang, Chen Gao, Jing Shi, Zhe Lin, Si Liu

Given the cycle, we propose several free augmentation strategies to help our model understand various editing requests given the imbalanced dataset.

Portrait Neural Radiance Fields from a Single Image

no code implementations10 Dec 2020 Chen Gao, YiChang Shih, Wei-Sheng Lai, Chia-Kai Liang, Jia-Bin Huang

We present a method for estimating Neural Radiance Fields (NeRF) from a single headshot portrait.


Group-Buying Recommendation for Social E-Commerce

1 code implementation14 Oct 2020 Jun Zhang, Chen Gao, Depeng Jin, Yong Li

Group-buying recommendation for social e-commerce, which recommends an item list when users want to launch a group, plays an important role in the group success ratio and sales.

NAS-DIP: Learning Deep Image Prior with Neural Architecture Search

1 code implementation ECCV 2020 Yun-Chun Chen, Chen Gao, Esther Robb, Jia-Bin Huang

Recent work has shown that the structure of deep convolutional neural networks can be used as a structured image prior for solving various inverse image restoration tasks.

Image Restoration Image-to-Image Translation +2

Disentangling User Interest and Conformity for Recommendation with Causal Embedding

3 code implementations19 Jun 2020 Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Depeng Jin, Yong Li

We further demonstrate that the learned embeddings successfully capture the desired causes, and show that DICE guarantees the robustness and interpretability of recommendation.

Causal Inference

Recapture as You Want

no code implementations2 Jun 2020 Chen Gao, Si Liu, Ran He, Shuicheng Yan, Bo Li

LGR module utilizes body skeleton knowledge to construct a layout graph that connects all relevant part features, where graph reasoning mechanism is used to propagate information among part nodes to mine their relations.

Bundle Recommendation with Graph Convolutional Networks

1 code implementation7 May 2020 Jianxin Chang, Chen Gao, Xiangnan He, Yong Li, Depeng Jin

Existing solutions integrate user-item interaction modeling into bundle recommendation by sharing model parameters or learning in a multi-task manner, which cannot explicitly model the affiliation between items and bundles, and fail to explore the decision-making when a user chooses bundles.

Decision Making

Price-aware Recommendation with Graph Convolutional Networks

1 code implementation9 Mar 2020 Yu Zheng, Chen Gao, Xiangnan He, Yong Li, Depeng Jin

Price, an important factor in marketing --- which determines whether a user will make the final purchase decision on an item --- surprisingly, has received relatively little scrutiny.

Collaborative Filtering Marketing +1

Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition

1 code implementation NeurIPS 2019 Jinwoo Choi, Chen Gao, Joseph C. E. Messou, Jia-Bin Huang

We validate the effectiveness of our method by transferring our pre-trained model to three different tasks, including action classification, temporal localization, and spatio-temporal action detection.

Action Classification Action Detection +4

AdversarialNAS: Adversarial Neural Architecture Search for GANs

1 code implementation CVPR 2020 Chen Gao, Yunpeng Chen, Si Liu, Zhenxiong Tan, Shuicheng Yan

In this paper, we propose an AdversarialNAS method specially tailored for Generative Adversarial Networks (GANs) to search for a superior generative model on the task of unconditional image generation.

Image Generation Neural Architecture Search +1

PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer

1 code implementation CVPR 2020 Wentao Jiang, Si Liu, Chen Gao, Jie Cao, Ran He, Jiashi Feng, Shuicheng Yan

In this paper, we address the makeup transfer task, which aims to transfer the makeup from a reference image to a source image.

UGAN: Untraceable GAN for Multi-Domain Face Translation

no code implementations26 Jul 2019 Defa Zhu, Si Liu, Wentao Jiang, Chen Gao, Tianyi Wu, Qaingchang Wang, Guodong Guo

To address this issue, we propose a method called Untraceable GAN, which has a novel source classifier to differentiate which domain an image is translated from, and determines whether the translated image still retains the characteristics of the source domain.

Image-to-Image Translation Translation

LambdaOpt: Learn to Regularize Recommender Models in Finer Levels

1 code implementation28 May 2019 Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang

We show how to employ LambdaOpt on matrix factorization, a classical model that is representative of a large family of recommender models.

Hyperparameter Optimization Recommendation Systems

Learning to Recommend with Multiple Cascading Behaviors

no code implementations21 Sep 2018 Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Lina Yao, Yang song, Depeng Jin

To fully exploit the signal in the data of multiple types of behaviors, we perform a joint optimization based on the multi-task learning framework, where the optimization on a behavior is treated as a task.

Multi-Task Learning Recommendation Systems

iCAN: Instance-Centric Attention Network for Human-Object Interaction Detection

4 code implementations30 Aug 2018 Chen Gao, Yuliang Zou, Jia-Bin Huang

Our core idea is that the appearance of a person or an object instance contains informative cues on which relevant parts of an image to attend to for facilitating interaction prediction.

Human-Object Interaction Detection Object

Panoramic Robust PCA for Foreground-Background Separation on Noisy, Free-Motion Camera Video

no code implementations18 Dec 2017 Brian E. Moore, Chen Gao, Raj Rao Nadakuditi

We perform extensive numerical experiments on both static and moving camera video subject to a variety of dense and sparse corruptions.

Augmented Robust PCA For Foreground-Background Separation on Noisy, Moving Camera Video

no code implementations27 Sep 2017 Chen Gao, Brian E. Moore, Raj Rao Nadakuditi

This work presents a novel approach for robust PCA with total variation regularization for foreground-background separation and denoising on noisy, moving camera video.


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