Search Results for author: Yang Cao

Found 68 papers, 30 papers with code

Grounding 3D Object Affordance from 2D Interactions in Images

1 code implementation18 Mar 2023 Yuhang Yang, Wei Zhai, Hongchen Luo, Yang Cao, Jiebo Luo, Zheng-Jun Zha

Comprehensive experiments on PIAD demonstrate the reliability of the proposed task and the superiority of our method.

Spatial-Aware Token for Weakly Supervised Object Localization

1 code implementation18 Mar 2023 Pingyu Wu, Wei Zhai, Yang Cao, Jiebo Luo, Zheng-Jun Zha

Specifically, a spatial token is first introduced in the input space to aggregate representations for localization task.

Uncertainty-Aware Optimal Transport for Semantically Coherent Out-of-Distribution Detection

1 code implementation18 Mar 2023 Fan Lu, Kai Zhu, Wei Zhai, Kecheng Zheng, Yang Cao

Semantically coherent out-of-distribution (SCOOD) detection aims to discern outliers from the intended data distribution with access to unlabeled extra set.

Cones: Concept Neurons in Diffusion Models for Customized Generation

2 code implementations9 Mar 2023 Zhiheng Liu, Ruili Feng, Kai Zhu, Yifei Zhang, Kecheng Zheng, Yu Liu, Deli Zhao, Jingren Zhou, Yang Cao

Concatenating multiple clusters of concept neurons can vividly generate all related concepts in a single image.

Traffic Scene Parsing through the TSP6K Dataset

no code implementations6 Mar 2023 Peng-Tao Jiang, YuQi Yang, Yang Cao, Qibin Hou, Ming-Ming Cheng, Chunhua Shen

Traffic scene parsing is one of the most important tasks to achieve intelligent cities.

Scene Parsing

P3DC-Shot: Prior-Driven Discrete Data Calibration for Nearest-Neighbor Few-Shot Classification

1 code implementation2 Jan 2023 Shuangmei Wang, Rui Ma, Tieru Wu, Yang Cao

Inspired by the distribution calibration technique which utilizes the distribution or statistics of the base classes to calibrate the data for few-shot tasks, we propose a novel discrete data calibration operation which is more suitable for NN-based few-shot classification.

Classification Few-Shot Learning

Detecting Change Intervals with Isolation Distributional Kernel

1 code implementation30 Dec 2022 Yang Cao, Ye Zhu, Kai Ming Ting, Flora D. Salim, Hong Xian Li, Gang Li

The data-dependent property and finite feature map of IDK enabled iCID to efficiently identify various types of change points in data streams with the tolerance of noise points.

Change Point Detection

Local Differential Privacy Image Generation Using Flow-based Deep Generative Models

no code implementations20 Dec 2022 Hisaichi Shibata, Shouhei Hanaoka, Yang Cao, Masatoshi Yoshikawa, Tomomi Takenaga, Yukihiro Nomura, Naoto Hayashi, Osamu Abe

To release and use medical images, we need an algorithm that can simultaneously protect privacy and preserve pathologies in medical images.

Image Generation

Application of Data Encryption in Chinese Named Entity Recognition

no code implementations31 Aug 2022 Kaifang Long, Jikun Dong, Shengyu Fan, Yanfang Geng, Yang Cao, Han Zhao, Hui Yu, Weizhi Xu

Recently, with the continuous development of deep learning, the performance of named entity recognition tasks has been dramatically improved.

Chinese Named Entity Recognition named-entity-recognition +1

Grounded Affordance from Exocentric View

2 code implementations28 Aug 2022 Hongchen Luo, Wei Zhai, Jing Zhang, Yang Cao, DaCheng Tao

Due to the diversity of interactive affordance, the uniqueness of different individuals leads to diverse interactions, which makes it difficult to establish an explicit link between object parts and affordance labels.

Human-Object Interaction Detection Transfer Learning

PrivateRec: Differentially Private Training and Serving for Federated News Recommendation

no code implementations18 Apr 2022 Ruixuan Liu, Yanlin Wang, Yang Cao, Lingjuan Lyu, Weike Pan, Yun Chen, Hong Chen

Collecting and training over sensitive personal data raise severe privacy concerns in personalized recommendation systems, and federated learning can potentially alleviate the problem by training models over decentralized user data. However, a theoretically private solution in both the training and serving stages of federated recommendation is essential but still lacking. Furthermore, naively applying differential privacy (DP) to the two stages in federated recommendation would fail to achieve a satisfactory trade-off between privacy and utility due to the high-dimensional characteristics of model gradients and hidden representations. In this work, we propose a federated news recommendation method for achieving a better utility in model training and online serving under a DP guarantee. We first clarify the DP definition over behavior data for each round in the life-circle of federated recommendation systems. Next, we propose a privacy-preserving online serving mechanism under this definition based on the idea of decomposing user embeddings with public basic vectors and perturbing the lower-dimensional combination coefficients.

Federated Learning News Recommendation +2

Network Shuffling: Privacy Amplification via Random Walks

no code implementations8 Apr 2022 Seng Pei Liew, Tsubasa Takahashi, Shun Takagi, Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa

However, introducing a centralized entity to the originally local privacy model loses some appeals of not having any centralized entity as in local differential privacy.

FAMLP: A Frequency-Aware MLP-Like Architecture For Domain Generalization

no code implementations24 Mar 2022 Kecheng Zheng, Yang Cao, Kai Zhu, Ruijing Zhao, Zheng-Jun Zha

However, its generalization performance to heterogeneous tasks is inferior to other architectures (e. g., CNNs and transformers) due to the extensive retention of domain information.

Domain Generalization

ProgressiveMotionSeg: Mutually Reinforced Framework for Event-Based Motion Segmentation

no code implementations22 Mar 2022 Jinze Chen, Yang Wang, Yang Cao, Feng Wu, Zheng-Jun Zha

Dynamic Vision Sensor (DVS) can asynchronously output the events reflecting apparent motion of objects with microsecond resolution, and shows great application potential in monitoring and other fields.

Denoising Motion Estimation +1

Location-Free Camouflage Generation Network

1 code implementation18 Mar 2022 Yangyang Li, Wei Zhai, Yang Cao, Zheng-Jun Zha

However, these methods struggle in 1) efficiently generating camouflage images using foreground and background with arbitrary structure; 2) camouflaging foreground objects to regions with multiple appearances (e. g. the junction of the vegetation and the mountains), which limit their practical application.

Learning Affordance Grounding from Exocentric Images

2 code implementations CVPR 2022 Hongchen Luo, Wei Zhai, Jing Zhang, Yang Cao, DaCheng Tao

To empower an agent with such ability, this paper proposes a task of affordance grounding from exocentric view, i. e., given exocentric human-object interaction and egocentric object images, learning the affordance knowledge of the object and transferring it to the egocentric image using only the affordance label as supervision.

Human-Object Interaction Detection Transfer Learning

Towards Data-Efficient Detection Transformers

2 code implementations17 Mar 2022 Wen Wang, Jing Zhang, Yang Cao, Yongliang Shen, DaCheng Tao

Besides, we introduce a simple yet effective label augmentation method to provide richer supervision and improve data efficiency.

Phrase-Based Affordance Detection via Cyclic Bilateral Interaction

4 code implementations24 Feb 2022 Liangsheng Lu, Wei Zhai, Hongchen Luo, Yu Kang, Yang Cao

In this paper, we explore to perceive affordance from a vision-language perspective and consider the challenging phrase-based affordance detection problem, i. e., given a set of phrases describing the action purposes, all the object regions in a scene with the same affordance should be detected.

Affordance Detection

Optimizing Random Mixup with Gaussian Differential Privacy

no code implementations14 Feb 2022 Donghao Li, Yang Cao, Yuan YAO

Recently, an algorithm called DPMix is proposed to release high-dimensional data after a random mixup of degree $m$ with differential privacy.

Self-Supervised Learning

Self-Paced Imbalance Rectification for Class Incremental Learning

no code implementations8 Feb 2022 Zhiheng Liu, Kai Zhu, Yang Cao

Exemplar-based class-incremental learning is to recognize new classes while not forgetting old ones, whose samples can only be saved in limited memory.

Class Incremental Learning Incremental Learning +1

Multi-Grained Spatio-Temporal Features Perceived Network for Event-Based Lip-Reading

no code implementations CVPR 2022 Ganchao Tan, Yang Wang, Han Han, Yang Cao, Feng Wu, Zheng-Jun Zha

To recognize words from the event data, we propose a novel Multi-grained Spatio-Temporal Features Perceived Network (MSTP) to perceive fine-grained spatio-temporal features from microsecond time-resolved event data.

Action Recognition Lip Reading

Dreaming To Prune Image Deraining Networks

no code implementations CVPR 2022 Weiqi Zou, Yang Wang, Xueyang Fu, Yang Cao

It is based on our observation that deep degradation representations can be clustered by degradation characteristics (types of rain) while independent of image content.

Model Compression Rain Removal

Background Activation Suppression for Weakly Supervised Object Localization

1 code implementation CVPR 2022 Pingyu Wu, Wei Zhai, Yang Cao

Existing FPM-based methods use cross-entropy (CE) to evaluate the foreground prediction map and to guide the learning of generator.

Weakly-Supervised Object Localization

Do What Nature Did To Us: Evolving Plastic Recurrent Neural Networks For Generalized Tasks

no code implementations29 Sep 2021 Fan Wang, Hao Tian, Haoyi Xiong, Hua Wu, Yang Cao, Yu Kang, Haifeng Wang

While artificial neural networks (ANNs) have been widely adopted in machine learning, researchers are increasingly obsessed by the gaps between ANNs and natural neural networks (NNNs).


FP-DETR: Detection Transformer Advanced by Fully Pre-training

no code implementations ICLR 2022 Wen Wang, Yang Cao, Jing Zhang, DaCheng Tao

To this end, we propose the task adapter which leverages self-attention to model the contextual relation between object query embedding.

object-detection Object Detection +1

Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning

2 code implementations8 Sep 2021 Fan Wang, Hao Tian, Haoyi Xiong, Hua Wu, Jie Fu, Yang Cao, Yu Kang, Haifeng Wang

In contrast, biological neural networks (BNNs) can adapt to various new tasks by continually updating the neural connections based on the inputs, which is aligned with the paradigm of learning effective learning rules in addition to static parameters, e. g., meta-learning.

Memorization Meta-Learning

Learning Visual Affordance Grounding from Demonstration Videos

no code implementations12 Aug 2021 Hongchen Luo, Wei Zhai, Jing Zhang, Yang Cao, DaCheng Tao

For the object branch, we introduce a semantic enhancement module (SEM) to make the network focus on different parts of the object according to the action classes and utilize a distillation loss to align the output features of the object branch with that of the video branch and transfer the knowledge in the video branch to the object branch.

Action Recognition

One-Shot Object Affordance Detection in the Wild

1 code implementation8 Aug 2021 Wei Zhai, Hongchen Luo, Jing Zhang, Yang Cao, DaCheng Tao

To empower robots with this ability in unseen scenarios, we first study the challenging one-shot affordance detection problem in this paper, i. e., given a support image that depicts the action purpose, all objects in a scene with the common affordance should be detected.

Action Recognition Affordance Detection +2

One-Shot Affordance Detection

2 code implementations28 Jun 2021 Hongchen Luo, Wei Zhai, Jing Zhang, Yang Cao, DaCheng Tao

To empower robots with this ability in unseen scenarios, we consider the challenging one-shot affordance detection problem in this paper, i. e., given a support image that depicts the action purpose, all objects in a scene with the common affordance should be detected.

Affordance Detection

Understanding the Interplay between Privacy and Robustness in Federated Learning

no code implementations13 Jun 2021 Yaowei Han, Yang Cao, Masatoshi Yoshikawa

Federated Learning (FL) is emerging as a promising paradigm of privacy-preserving machine learning, which trains an algorithm across multiple clients without exchanging their data samples.

Adversarial Robustness Federated Learning +1

FL-Market: Trading Private Models in Federated Learning

1 code implementation8 Jun 2021 Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa, Huizhong Li, Qiang Yan

FL-Market decouples ML from the need to centrally gather training data on the broker's side using federated learning, an emerging privacy-preserving ML paradigm in which data owners collaboratively train an ML model by uploading local gradients (to be aggregated into a global gradient for model updating).

Federated Learning Privacy Preserving

FakeMix Augmentation Improves Transparent Object Detection

1 code implementation24 Mar 2021 Yang Cao, Zhengqiang Zhang, Enze Xie, Qibin Hou, Kai Zhao, Xiangui Luo, Jian Tuo

However, these methods usually encounter boundary-related imbalance problem, leading to limited generation capability.

Data Augmentation object-detection +2

FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation

no code implementations9 Feb 2021 Chuhan Wu, Fangzhao Wu, Yang Cao, Yongfeng Huang, Xing Xie

To incorporate high-order user-item interactions, we propose a user-item graph expansion method that can find neighboring users with co-interacted items and exchange their embeddings for expanding the local user-item graphs in a privacy-preserving way.

Privacy Preserving

Transparent Contribution Evaluation for Secure Federated Learning on Blockchain

no code implementations26 Jan 2021 Shuaicheng Ma, Yang Cao, Li Xiong

In this work, we propose a blockchain-based federated learning framework and a protocol to transparently evaluate each participant's contribution.

BIG-bench Machine Learning Federated Learning

Quantifying the Privacy-Utility Trade-offs in COVID-19 Contact Tracing Apps

no code implementations24 Dec 2020 Patrick Ocheja, Yang Cao, Shiyao Ding, Masatoshi Yoshikawa

How to contain the spread of the COVID-19 virus is a major concern for most countries.

Computers and Society Cryptography and Security 68P27 H.3.4

PCT-TEE: Trajectory-based Private Contact Tracing System with Trusted Execution Environment

1 code implementation7 Dec 2020 Fumiyuki Kato, Yang Cao, Yoshikawa Masatoshi

To this end, we design a TEE-based system with flexible trajectory data encoding algorithms.

Cryptography and Security Computers and Society

FLAME: Differentially Private Federated Learning in the Shuffle Model

1 code implementation17 Sep 2020 Ruixuan Liu, Yang Cao, Hong Chen, Ruoyang Guo, Masatoshi Yoshikawa

In this work, by leveraging the \textit{privacy amplification} effect in the recently proposed shuffle model of differential privacy, we achieve the best of two worlds, i. e., accuracy in the curator model and strong privacy without relying on any trusted party.

Federated Learning

Finding Acceptable Parameter Regions of Stochastic Hill functions for Multisite Phosphorylation Mechanism

no code implementations14 Sep 2020 Minghan Chen, Mansooreh Ahmadian, Layne Watson, Yang Cao

To reduce model complexity, this work aims to simplify the multisite phosphorylation mechanism by a stochastic Hill function model.

Stochastic Optimization

Nighttime Dehazing with a Synthetic Benchmark

1 code implementation10 Aug 2020 Jing Zhang, Yang Cao, Zheng-Jun Zha, DaCheng Tao

To address this issue, we propose a novel synthetic method called 3R to simulate nighttime hazy images from daytime clear images, which first reconstructs the scene geometry, then simulates the light rays and object reflectance, and finally renders the haze effects.

P3GM: Private High-Dimensional Data Release via Privacy Preserving Phased Generative Model

2 code implementations22 Jun 2020 Shun Takagi, Tsubasa Takahashi, Yang Cao, Masatoshi Yoshikawa

The state-of-the-art approach for this problem is to build a generative model under differential privacy, which offers a rigorous privacy guarantee.

Privacy Preserving

PGLP: Customizable and Rigorous Location Privacy through Policy Graph

3 code implementations4 May 2020 Yang Cao, Yonghui Xiao, Shun Takagi, Li Xiong, Masatoshi Yoshikawa, Yilin Shen, Jinfei Liu, Hongxia Jin, Xiaofeng Xu

Third, we design a private location trace release framework that pipelines the detection of location exposure, policy graph repair, and private trajectory release with customizable and rigorous location privacy.

Cryptography and Security Computers and Society

PANDA: Policy-aware Location Privacy for Epidemic Surveillance

3 code implementations1 May 2020 Yang Cao, Shun Takagi, Yonghui Xiao, Li Xiong, Masatoshi Yoshikawa

Our system has three primary functions for epidemic surveillance: location monitoring, epidemic analysis, and contact tracing.

Databases Cryptography and Security

Self-Supervised Tuning for Few-Shot Segmentation

no code implementations12 Apr 2020 Kai Zhu, Wei Zhai, Zheng-Jun Zha, Yang Cao

Few-shot segmentation aims at assigning a category label to each image pixel with few annotated samples.


FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection

no code implementations24 Mar 2020 Ruixuan Liu, Yang Cao, Masatoshi Yoshikawa, Hong Chen

To prevent privacy leakages from gradients that are calculated on users' sensitive data, local differential privacy (LDP) has been considered as a privacy guarantee in federated SGD recently.

Federated Learning

Sensor-Augmented Neural Adaptive Bitrate Video Streaming on UAVs

no code implementations23 Sep 2019 Xuedou Xiao, Wei Wang, Taobin Chen, Yang Cao, Tao Jiang, Qian Zhang

In this paper, we present SA-ABR, a new sensor-augmented system that generates ABR video streaming algorithms with the assistance of various kinds of inherent sensor data that are used to pilot UAVs.

EGNet:Edge Guidance Network for Salient Object Detection

no code implementations22 Aug 2019 Jia-Xing Zhao, Jiang-Jiang Liu, Den-Ping Fan, Yang Cao, Jufeng Yang, Ming-Ming Cheng

In the second step, we integrate the local edge information and global location information to obtain the salient edge features.

object-detection RGB Salient Object Detection +1

One-Shot Texture Retrieval with Global Context Metric

no code implementations16 May 2019 Kai Zhu, Wei Zhai, Zheng-Jun Zha, Yang Cao

In this paper, we tackle one-shot texture retrieval: given an example of a new reference texture, detect and segment all the pixels of the same texture category within an arbitrary image.


Deep Time-Frequency Representation and Progressive Decision Fusion for ECG Classification

no code implementations19 Jan 2019 Jing Zhang, Jing Tian, Yang Cao, Yuxiang Yang, Xiaobin Xu

Early recognition of abnormal rhythms in ECG signals is crucial for monitoring and diagnosing patients' cardiac conditions, increasing the success rate of the treatment.

ECG Classification General Classification

Enhanced-alignment Measure for Binary Foreground Map Evaluation

2 code implementations26 May 2018 Deng-Ping Fan, Cheng Gong, Yang Cao, Bo Ren, Ming-Ming Cheng, Ali Borji

The existing binary foreground map (FM) measures to address various types of errors in either pixel-wise or structural ways.

Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit

no code implementations11 Feb 2018 Yang Cao, Zheng Wen, Branislav Kveton, Yao Xie

Multi-armed bandit (MAB) is a class of online learning problems where a learning agent aims to maximize its expected cumulative reward while repeatedly selecting to pull arms with unknown reward distributions.

Change Detection

Fully Point-wise Convolutional Neural Network for Modeling Statistical Regularities in Natural Images

no code implementations19 Jan 2018 Jing Zhang, Yang Cao, Yang Wang, Chenglin Wen, Chang Wen Chen

Specifically, we propose to randomly shuffle the pixels in the origin images and leverage the shuffled image as input to make CNN more concerned with the statistical properties.

Color Constancy Image Dehazing

Quantifying Differential Privacy in Continuous Data Release under Temporal Correlations

2 code implementations29 Nov 2017 Yang Cao, Masatoshi Yoshikawa, Yonghui Xiao, Li Xiong

Our analysis reveals that, the event-level privacy loss of a DP mechanism may \textit{increase over time}.


Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior

no code implementations CVPR 2017 Jing Zhang, Yang Cao, Shuai Fang, Yu Kang, Chang Wen Chen

Then, we propose a simple but effective image prior, maximum reflectance prior, to estimate the varying ambient illumination.

Nearly second-order asymptotic optimality of sequential change-point detection with one-sample updates

no code implementations19 May 2017 Yang Cao, Liyan Xie, Yao Xie, Huan Xu

Our proof is achieved by making a connection between sequential change-point and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm.

Change Point Detection

Quantifying Differential Privacy under Temporal Correlations

2 code implementations24 Oct 2016 Yang Cao, Masatoshi Yoshikawa, Yonghui Xiao, Li Xiong

Our analysis reveals that the privacy leakage of a DP mechanism may accumulate and increase over time.

Databases Cryptography and Security

Nighttime Haze Removal with Illumination Correction

no code implementations5 Jun 2016 Jing Zhang, Yang Cao, Zengfu Wang

ii) Then it achieves a color-balance result by performing a color correction step after estimating the color characteristics of the incident light.

Multi-Sensor Slope Change Detection

no code implementations1 Sep 2015 Yang Cao, Yao Xie, Nagi Gebraeel

Observations are assumed to be initially normal random variables with known constant means and variances.

Change Detection

Categorical Matrix Completion

no code implementations2 Jul 2015 Yang Cao, Yao Xie

We recover a low-rank matrix $X$ by maximizing the likelihood ratio with a constraint on the nuclear norm of $X$, and the observations are mapped from entries of $X$ through multiple link functions.

Matrix Completion

Sketching for Sequential Change-Point Detection

no code implementations25 May 2015 Yang Cao, Andrew Thompson, Meng Wang, Yao Xie

We study sequential change-point detection procedures based on linear sketches of high-dimensional signal vectors using generalized likelihood ratio (GLR) statistics.

Change Point Detection

Poisson Matrix Recovery and Completion

no code implementations20 Apr 2015 Yang Cao, Yao Xie

We extend the theory of low-rank matrix recovery and completion to the case when Poisson observations for a linear combination or a subset of the entries of a matrix are available, which arises in various applications with count data.

Matrix Completion

Poisson Matrix Completion

no code implementations26 Jan 2015 Yang Cao, Yao Xie

We extend the theory of matrix completion to the case where we make Poisson observations for a subset of entries of a low-rank matrix.

Matrix Completion

Fast Algorithm for Low-rank matrix recovery in Poisson noise

no code implementations2 Jul 2014 Yang Cao, Yao Xie

This paper describes a fast algorithm for recovering low-rank matrices from their linear measurements contaminated with Poisson noise: the Poisson noise Maximum Likelihood Singular Value thresholding (PMLSV) algorithm.

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