How human interact with objects depends on the functional roles of the t...
Neural networks have been able to generate high-quality single-sentence
...
Today's blockchains suffer from low throughput and high latency, which
i...
Knowledge distillation (KD) is a promising technique for model compressi...
The rapid rise in cloud computing has resulted in an alarming increase i...
Although both self-supervised single-frame and multi-frame depth estimat...
Federated learning (FL) provides a variety of privacy advantages by allo...
Deep normal estimators have made great strides on synthetic benchmarks.
...
Harnessing logical reasoning ability is a comprehensive natural language...
Distributed machine learning paradigms, such as federated learning, have...
Data valuation is an essential task in a data marketplace. It aims at fa...
Although recent Siamese network-based trackers have achieved impressive
...
Translation suggestion (TS) models are used to automatically provide
alt...
In this paper, we present the Multi-Forgery Detection Challenge held
con...
Enhancing existing transmission lines is a useful tool to combat transmi...
As a common security tool, visible watermarking has been widely applied ...
Proteins interact to form complexes to carry out essential biological
fu...
Protein complexes are macromolecules essential to the functioning and
we...
Although existing monocular depth estimation methods have made great
pro...
We propose volume-preserving networks (VPNets) for learning unknown
sour...
Federated Learning (FL) framework brings privacy benefits to distributed...
Token-level adaptive training approaches can alleviate the token imbalan...
Hierarchical multi-granularity classification (HMC) assigns hierarchical...
To fully support vertical industries, 5G and its corresponding channel c...
Aspect category sentiment analysis has attracted increasing research
att...
Federated Learning (FL) enables multiple distributed clients (e.g., mobi...
With the growing popularity of Android devices, Android malware is serio...
As facial interaction systems are prevalently deployed, security and
rel...
Named entity recognition (NER) of chemicals and drugs is a critical doma...
Natural language inference (NLI) is a fundamental NLP task, investigatin...
Machine reading is a fundamental task for testing the capability of natu...
Multi-source unsupervised domain adaptation (MS-UDA) for sentiment analy...
Recently, the vulnerability of DNN-based audio systems to adversarial at...
As the popularity of voice user interface (VUI) exploded in recent years...
Federated learning is a recently proposed paradigm that enables multiple...
Deep learning models achieve impressive performance for skeleton-based h...
In this paper, we build a speech privacy attack that exploits speech
rev...
Advances in Deep Learning have recently made it possible to recover full...
When purchasing appearance-first products, e.g., clothes, product appear...
Consensus mechanisms used by popular distributed ledgers are highly scal...
Bitcoin uses blockchain technology and proof-of-work (PoW) mechanism whe...
The ultimatum game has been a prominent paradigm in studying the evoluti...
Mode collapse is one of the key challenges in the training of Generative...
Person identification in the wild is very challenging due to great varia...
We propose to synthesize feasible caging grasps for a target object thro...
Time series prediction has been studied in a variety of domains. However...
In this paper, we seek to better understand Android obfuscation and depi...
Human skeleton joints are popular for action analysis since they can be
...
Recent advances in Deep Learning show the existence of image-agnostic
qu...
In video-based action recognition, viewpoint variations often pose major...