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Found 80 papers, 20 papers with code
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.
From Contexts to Locality: Ultra-high Resolution Image Segmentation via Locality-aware Contextual Correlation
Ultra-high resolution image segmentation has raised increasing interests in recent years due to its realistic applications.
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
In this paper, we argue that online map learning, which dynamically constructs the HD maps based on local sensor observations, is a more scalable way to provide semantic and geometry priors to self-driving vehicles than traditional pre-annotated HD maps.
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 #3 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
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.
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.
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.
EVIDENCEMINER: Textual Evidence Discovery for Life Sciences
EVIDENCEMINER is constructed in a completely automated way without any human effort for training data annotation.
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.
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 #5 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.
Electron Microscopy Image Segmentation
Image Reconstruction
+1
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
Inspired by AFS, we propose a defense framework based on Adversarial Feature Genome (AFG), which can detect and correctly classify adversarial examples into original classes simultaneously.
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.
