Search Results for author:
Found 109 papers, 31 papers with code
Semantic-aware One-shot Face Re-enactment with Dense Correspondence Estimation
One-shot face re-enactment is a challenging task due to the identity mismatch between source and driving faces.
Monocular BEV Perception of Road Scenes via Front-to-Top View Projection
We propose a front-to-top view projection (FTVP) module, which takes the constraint of cycle consistency between views into account and makes full use of their correlation to strengthen the view transformation and scene understanding.
Trackerless freehand ultrasound with sequence modelling and auxiliary transformation over past and future frames
Little benefit was observed by adding frames more than one second away from the predicted transformation, with or without LSTM-based RNNs.
GAN-based Facial Attribute Manipulation
Facial Attribute Manipulation (FAM) aims to aesthetically modify a given face image to render desired attributes, which has received significant attention due to its broad practical applications ranging from digital entertainment to biometric forensics.
Supervised Contrastive Learning with Tree-Structured Parzen Estimator Bayesian Optimization for Imbalanced Tabular Data
To solve this problem, we propose a Supervised Contrastive Learning (SCL) method with Tree-structured Parzen Estimator (TPE) technique for imbalanced tabular datasets.
FedDef: Defense Against Gradient Leakage in Federated Learning-based Network Intrusion Detection Systems
Deep learning (DL) methods have been widely applied to anomaly-based network intrusion detection system (NIDS) to detect malicious traffic.
TPGNN: Learning High-order Information in Dynamic Graphs via Temporal Propagation
We argue that when learning high-order information from temporal graphs, we encounter two challenges, i. e., computational inefficiency and over-smoothing, that cannot be solved by conventional techniques applied on static graphs.
Heterogeneous Graph Contrastive Multi-view Learning
How to mitigate the sampling bias for heterogeneous GCL is another important problem.
IdeaReader: A Machine Reading System for Understanding the Idea Flow of Scientific Publications
Understanding the origin and influence of the publication's idea is critical to conducting scientific research.
On the Privacy Risks of Cell-Based NAS Architectures
Existing studies on neural architecture search (NAS) mainly focus on efficiently and effectively searching for network architectures with better performance.
Disentangled Graph Contrastive Learning for Review-based Recommendation
In review-based recommendation methods, review data is considered as auxiliary information that can improve the quality of learned user/item or interaction representations for the user rating prediction task.
Improving Distantly Supervised Relation Extraction by Natural Language Inference
To reduce human annotations for relation extraction (RE) tasks, distantly supervised approaches have been proposed, while struggling with low performance.
Adaptive Domain Interest Network for Multi-domain Recommendation
Industrial recommender systems usually hold data from multiple business scenarios and are expected to provide recommendation services for these scenarios simultaneously.
Towards future directions in data-integrative supervised prediction of human aging-related genes
Here, we evaluate whether analyzing a weighted dynamic aging-specific subnetwork inferred from newer GE and PPIN data improves prediction accuracy upon analyzing the best current subnetwork inferred from outdated data.
Acceleration-guided Acoustic Signal Denoising Framework Based on Learnable Wavelet Transform Applied to Slab Track Condition Monitoring
Therefore, only acoustic sensors (non-intrusive) need to be installed during the application phase, which is convenient and crucial for the condition monitoring of safety-critical infrastructure.
Multiple-access relay stations for long-haul fiber-optic radio frequency transfer
We report on the realization of a long-haul radio frequency (RF) transfer scheme by using multiple-access relay stations (MARSs).
AnyFace: Free-style Text-to-Face Synthesis and Manipulation
AnyFace can achieve high-quality, high-resolution, and high-diversity face synthesis and manipulation results without any constraints on the number and content of input captions.
Learning Disentangled Representation for One-shot Progressive Face Swapping
In addition, semantic information is introduced into the semantic-guided fusion module to control the swapped area and model the pose and expression more accurately.
Towards Benchmarking and Evaluating Deepfake Detection
Deepfake detection automatically recognizes the manipulated medias through the analysis of the difference between manipulated and non-altered videos.
Voice-Face Homogeneity Tells Deepfake
To this end, a voice-face matching method is devised to measure the matching degree of these two.
Quantum Deep Learning for Mutant COVID-19 Strain Prediction
New COVID-19 epidemic strains like Delta and Omicron with increased transmissibility and pathogenicity emerge and spread across the whole world rapidly while causing high mortality during the pandemic period.
Distantly Supervised Named Entity Recognition via Confidence-Based Multi-Class Positive and Unlabeled Learning
In this paper, we study the named entity recognition (NER) problem under distant supervision.
Approximate Nearest Neighbor Search under Neural Similarity Metric for Large-Scale Recommendation
In this paper, we propose a novel method to extend ANN search to arbitrary matching functions, e. g., a deep neural network.
MOST-Net: A Memory Oriented Style Transfer Network for Face Sketch Synthesis
Furthermore, we design a novel Memory Refinement Loss (MR Loss) for feature alignment in the memory module, which enhances the accuracy of memory slots in an unsupervised manner.
CPTAM: Constituency Parse Tree Aggregation Method
This paper adopts the truth discovery idea to aggregate constituency parse trees from different parsers by estimating their reliability in the absence of ground truth.
Biphasic Face Photo-Sketch Synthesis via Semantic-Driven Generative Adversarial Network with Graph Representation Learning
In addition, to improve the fidelity of the generated results, we leverage the semantic layouts to construct two types of Representational Graphs which indicate the intra-class semantic features and inter-class structural features of the synthesized images.
IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes
While most works focus on single-object or agent-object visual functionality and affordances, our work proposes to study a new kind of visual relationship that is also important to perceive and model -- inter-object functional relationships (e. g., a switch on the wall turns on or off the light, a remote control operates the TV).
Black-box Adversarial Attacks on Commercial Speech Platforms with Minimal Information
For commercial cloud speech APIs, we propose Occam, a decision-only black-box adversarial attack, where only final decisions are available to the adversary.
A Unified Framework for Biphasic Facial Age Translation with Noisy-Semantic Guided Generative Adversarial Networks
Biphasic facial age translation aims at predicting the appearance of the input face at any age.
Truth Discovery in Sequence Labels from Crowds
The proposed Aggregation method for Sequential Labels from Crowds ($AggSLC$) jointly considers the characteristics of sequential labeling tasks, workers' reliabilities, and advanced machine learning techniques.
Ultra-high Resolution Image Segmentation via Locality-aware Context Fusion and Alternating Local Enhancement
In particular, we introduce a novel locality-aware context fusion based segmentation model to process local patches, where the relevance between local patch and its various contexts are jointly and complementarily utilized to handle the semantic regions with large variations.
Towards Balanced Learning for Instance Recognition
In this work, we carefully revisit the standard training practice of detectors, and find that the detection performance is often limited by the imbalance during the training process, which generally consists in three levels - sample level, feature level, and objective level.
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks
We also evaluate the effectiveness of our attack under two defenses: one is well-designed adversarial graph detector and the other is that the target GNN model itself is equipped with a defense to prevent adversarial graph generation.
QA-Driven Zero-shot Slot Filling with Weak Supervision Pretraining
To address this problem, we introduce QA-driven slot filling (QASF), which extracts slot-filler spans from utterances with a span-based QA model.
HDMapNet: An Online HD Map Construction and Evaluation Framework
By introducing the method and metrics, we invite the community to study this novel map learning problem.
Contrastive Learning for Cold-Start Recommendation
It aims to maximize the mutual dependencies between item content and collaborative signals.
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network
For videos, such negative transfer could be triggered by both spatial and temporal features, which leads to a more challenging Partial Video Domain Adaptation (PVDA) problem.
Face Sketch Synthesis via Semantic-Driven Generative Adversarial Network
To tackle these challenges, we propose a novel Semantic-Driven Generative Adversarial Network (SDGAN) which embeds global structure-level style injection and local class-level knowledge re-weighting.
Realtime Robust Malicious Traffic Detection via Frequency Domain Analysis
To this end, we propose Whisper, a realtime ML based malicious traffic detection system that achieves both high accuracy and high throughput by utilizing frequency domain features.
AdaptCL: Efficient Collaborative Learning with Dynamic and Adaptive Pruning
In a highly heterogeneous environment, AdaptCL achieves a training speedup of 6. 2x with a slight loss of accuracy.
Class agnostic moving target detection by color and location prediction of moving area
Then, the color and location probability map of the moving area will be calculated through maximum a posteriori probability.
Projecting Your View Attentively: Monocular Road Scene Layout Estimation via Cross-View Transformation
Furthermore, our model runs at 35 FPS on a single GPU, which is efficient and applicable for real-time panorama HD map reconstruction.
Autonomous Driving
Monocular Cross-View Road Scene Parsing(Road)
+1
CARTL: Cooperative Adversarially-Robust Transfer Learning
In deep learning, a typical strategy for transfer learning is to freeze the early layers of a pre-trained model and fine-tune the rest of its layers on the target domain.
DFGC 2021: A DeepFake Game Competition
This competition provides a common platform for benchmarking the adversarial game between current state-of-the-art DeepFake creation and detection methods.
One Shot Face Swapping on Megapixels
Extensive experiments demonstrate the superiority of MegaFS and the first megapixel level face swapping database is released for research on DeepFake detection and face image editing in the public domain.
Ranked #7 on
Face Swapping
on FaceForensics++
SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models
Single image super-resolution (SISR) aims to reconstruct high-resolution (HR) images from the given low-resolution (LR) ones, which is an ill-posed problem because one LR image corresponds to multiple HR images.
Few-shot Intent Classification and Slot Filling with Retrieved Examples
Few-shot learning arises in important practical scenarios, such as when a natural language understanding system needs to learn new semantic labels for an emerging, resource-scarce domain.
Free-form Description Guided 3D Visual Graph Network for Object Grounding in Point Cloud
There are three main challenges in 3D object grounding: to find the main focus in the complex and diverse description; to understand the point cloud scene; and to locate the target object.
COSINE: A Web Server for Clonal and Subclonal Structure Inference and Evolution in Cancer Genomics
In the past decade, a variety of methods have been developed for subclonal reconstruction using bulk tumor sequencing data.
Optical properties of elongated conducting grains
Extremely elongated, conducting dust particles (also known as metallic "needles" or "whiskers") are seen in carbonaceous chondrites and in samples brought back from the Itokawa asteroid.
Astrophysics of Galaxies
Data Poisoning Attacks and Defenses to Crowdsourcing Systems
Our empirical results show that the proposed defenses can substantially reduce the estimation errors of the data poisoning attacks.
Truncation-Free Matching System for Display Advertising at Alibaba
When receiving a user request, matching system (i) finds the crowds that the user belongs to; (ii) retrieves all ads that have targeted those crowds.
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis
Particularly, the localized adversarial examples only perturb a small and contiguous region of the target object, so that they are robust and effective in both digital and physical worlds.
Data Poisoning Attacks to Deep Learning Based Recommender Systems
Specifically, we formulate our attack as an optimization problem, such that the injected ratings would maximize the number of normal users to whom the target items are recommended.
Automatic Historical Feature Generation through Tree-based Method in Ads Prediction
Historical features are important in ads click-through rate (CTR) prediction, because they account for past engagements between users and ads.
Robust Attacks on Deep Learning Face Recognition in the Physical World
Deep neural networks (DNNs) have been increasingly used in face recognition (FR) systems.
Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?
Generative Adversarial Networks (GANs) with style-based generators (e. g. StyleGAN) successfully enable semantic control over image synthesis, and recent studies have also revealed that interpretable image translations could be obtained by modifying the latent code.
OptSLA: an Optimization-Based Approach for Sequential Label Aggregation
Our results show that the proposed OptSLA outperforms the state-of-the-art aggregation methods, and the results are easier to interpret.
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search
The experiments on ImageNet verify such path distillation method can improve the convergence ratio and performance of the hypernetwork, as well as boosting the training of subnetworks.
Manifold learning-based feature extraction for structural defect reconstruction
Data-driven quantitative defect reconstructions using ultrasonic guided waves has recently demonstrated great potential in the area of non-destructive testing.
A novel combination of theoretical analysis and data-driven method for reconstruction of structural defects
To address this issue, a novel approach to quantitative reconstruction of defects using the integration of data-driven method with the guided wave scattering analysis has been proposed in this paper.
Computational Engineering, Finance, and Science J.2
Removing Backdoor-Based Watermarks in Neural Networks with Limited Data
In this paper, we benchmark the robustness of watermarking, and propose a novel backdoor-based watermark removal framework using limited data, dubbed WILD.
Low-light Image Restoration with Short- and Long-exposure Raw Pairs
Using our data generation method and the proposed LSFNet, we can recover the details and color of the original scene, and improve the low-light image quality effectively.
EVIDENCEMINER: Textual Evidence Discovery for Life Sciences
EVIDENCEMINER is constructed in a completely automated way without any human effort for training data annotation.
Quasi-Dense Similarity Learning for Multiple Object Tracking
Compared to methods with similar detectors, it boosts almost 10 points of MOTA and significantly decreases the number of ID switches on BDD100K and Waymo datasets.
Ranked #1 on
One-Shot Object Detection
on PASCAL VOC 2012 val
Reference-guided Face Component Editing
Face portrait editing has achieved great progress in recent years.
Improved supervised prediction of aging-related genes via weighted dynamic network analysis
Instead, we recently inferred a dynamic aging-specific subnetwork using a methodologically more advanced notion of network propagation (NP), which improved upon Induced dynamic aging-specific subnetwork in a different task, that of unsupervised analyses of the aging process.
Partially-Typed NER Datasets Integration: Connecting Practice to Theory
While typical named entity recognition (NER) models require the training set to be annotated with all target types, each available datasets may only cover a part of them.
Spatio-Temporal Dual Affine Differential Invariant for Skeleton-based Action Recognition
The dynamics of human skeletons have significant information for the task of action recognition.
Negative Margin Matters: Understanding Margin in Few-shot Classification
This paper introduces a negative margin loss to metric learning based few-shot learning methods.
Beyond Camera Motion Blur Removing: How to Handle Outliers in Deblurring
In this paper, we propose a novel method to handle camera motion blur with outliers.
Spatial-Adaptive Network for Single Image Denoising
An encoder-decoder structure with a context block is introduced to capture multiscale information.
Ranked #7 on
Image Denoising
on DND
(using extra training data)
Dual affine moment invariants
In this paper, we propose a general framework to derive moment invariants under DAT for objects in M-dimensional space with N channels, which can be called dual-affine moment invariants (DAMI).
A3GAN: An Attribute-aware Attentive Generative Adversarial Network for Face Aging
Face aging, which aims at aesthetically rendering a given face to predict its future appearance, has received significant research attention in recent years.
Adversarial Example in Remote Sensing Image Recognition
This added adversarial perturbation image is called an adversarial example, which poses a serious security problem for systems based on CNN model recognition results.
HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories
With the massive number of repositories available, there is a pressing need for topic-based search.
A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddings
Large, pre-trained generative models have been increasingly popular and useful to both the research and wider communities.
Improving Relation Extraction with Knowledge-attention
While attention mechanisms have been proven to be effective in many NLP tasks, majority of them are data-driven.
Supervised prediction of aging-related genes from a context-specific protein interaction subnetwork
In a systematic and comprehensive evaluation, we find that in many of the evaluation tests: (i) using an aging-specific subnetwork indeed yields more accurate aging-related gene predictions than using the entire network, and (ii) predictive methods from our framework that have not previously been used for supervised prediction of aging-related genes outperform existing prominent methods for the same purpose.
TeraVR empowers precise reconstruction of complete 3-D neuronal morphology in the whole brain
Neuron morphology is recognized as a key determinant of cell type, yet the quantitative profiling of a mammalian neuron’s complete three-dimensional (3-D) morphology remains arduous when the neuron has complex arborization and long projection.
Adversarial Learning Semantic Volume for 2D/3D Face Shape Regression in the Wild
Then, an end-to-end pipeline is designed to jointly regress the proposed volumetric representation and the coordinate vector.
Ranked #3 on
Face Alignment
on AFLW2000-3D
Causality Extraction based on Self-Attentive BiLSTM-CRF with Transferred Embeddings
Causality extraction from natural language texts is a challenging open problem in artificial intelligence.
Age Progression and Regression with Spatial Attention Modules
Age progression and regression refers to aesthetically render-ing a given face image to present effects of face aging and rejuvenation, respectively.
Network Service Dependencies in Commodity Internet-of-Things Devices
We continue to see increasingly widespread deployment of IoT devices, with apparent intent to embed them in our built environment likely to accelerate if smart city and related programmes succeed.
Networking and Internet Architecture
Understanding the Importance of Single Directions via Representative Substitution
Understanding the internal representations of deep neural networks (DNNs) is crucal to explain their behavior.
A Data-driven Adversarial Examples Recognition Framework via Adversarial Feature Genome
In this regard, we propose the Adversarial Feature Genome (AFG), a novel type of data that contains both the differences and features about classes.
Strike (with) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects
Using our framework and a self-assembled dataset of 3D objects, we investigate the vulnerability of DNNs to OoD poses of well-known objects in ImageNet.
Understanding the Importance of Single Directions via Representative Substitution
Understanding the internal representations of deep neural networks (DNNs) is crucal to explain their behavior.
A Regressive Convolution Neural network and Support Vector Regression Model for Electricity Consumption Forecasting
Electricity consumption forecasting has important implications for the mineral companies on guiding quarterly work, normal power system operation, and the management.
Electricity consumption forecasting method based on MPSO-BP neural network model
This paper deals with the problem of the electricity consumption forecasting method.
Finding Similar Medical Questions from Question Answering Websites
Patients who have medical information demands tend to post questions about their health conditions on these crowdsourced Q&A websites and get answers from other users.
Attribute-aware Face Aging with Wavelet-based Generative Adversarial Networks
Since it is difficult to collect face images of the same subject over a long range of age span, most existing face aging methods resort to unpaired datasets to learn age mappings.
Differential and integral invariants under Mobius transformation
According to the Liouville Theorem, an important part of the conformal transformation is the Mobius transformation, so we focus on Mobius transformation and propose two differential expressions that are invariable under 2-D and 3-D Mobius transformation respectively.
Joint Voxel and Coordinate Regression for Accurate 3D Facial Landmark Localization
Then, a stacked hourglass network is adopted to estimate the volumetric representation from coarse to fine, followed by a 3D convolution network that takes the estimated volume as input and regresses 3D coordinates of the face shape.
Ranked #1 on
3D Facial Landmark Localization
on AFLW2000-3D
Global and Local Consistent Age Generative Adversarial Networks
To utilize both global and local facial information, we propose a Global and Local Consistent Age Generative Adversarial Network (GLCA-GAN).
Learning Deep Similarity Models with Focus Ranking for Fabric Image Retrieval
Fabric image retrieval is beneficial to many applications including clothing searching, online shopping and cloth modeling.
Authorship attribution of source code by using back propagation neural network based on particle swarm optimization
Then these metrics are input to neural network for supervised learning, the weights of which are output by PSO and BP hybrid algorithm.
Deep Supervised Discrete Hashing
Benefit from recent advances in deep learning, deep hashing methods have achieved promising results for image retrieval.
Combining Data-driven and Model-driven Methods for Robust Facial Landmark Detection
This Estimation-Correction-Tuning process perfectly combines the advantages of the global robustness of data-driven method (FCN), outlier correction capability of model-driven method (PDM) and non-parametric optimization of RLMS.
Learning Word Sense Embeddings from Word Sense Definitions
Word embeddings play a significant role in many modern NLP systems.
Distributed Parameter Map-Reduce
But the premise of inference is that the map procedure holds parameters for all features in the sample.
Comparison of the Impact of Word Segmentation on Name Tagging for Chinese and Japanese
As long as (2) is ensured, the performance of word segmentation does not have appreciable impact on Chinese and Japanese name tagging.
