In this paper, we propose a new paradigm, named Historical Object Predic...
With the growing needs of online A/B testing to support the innovation i...
Artificial Intelligence (AI) has made incredible progress recently. On t...
Predicting the next location is a highly valuable and common need in man...
Alzheimer's Disease (AD) causes a continuous decline in memory, thinking...
Touch-based fingerprint biometrics is one of the most popular biometric
...
Human brains respond to semantic features of presented stimuli with diff...
Monitoring sustainable development goals requires accurate and timely
so...
Video-Text Retrieval (VTR) aims to search for the most relevant video re...
Recent large-scale generative models learned on big data are capable of
...
Despite the significant progress in 6-DoF visual localization, researche...
The multivariate adaptive regression spline (MARS) is one of the popular...
The deep reinforcement learning (DRL) algorithm works brilliantly on sol...
The visual dimension of cities has been a fundamental subject in urban
s...
When facing objects/files of differing sizes in content delivery network...
Hierarchical semantic structures, naturally existing in real-world datas...
Diffusion models, which learn to reverse a signal destruction process to...
The classification and regression tree (CART) and Random Forest (RF) are...
In this paper, we provide the observation that too few queries assigned ...
Existing GAN inversion methods work brilliantly for high-quality image
r...
Deep Convolutional Neural Networks (DCNNs) have exhibited impressive
per...
Face super-resolution is a domain-specific image super-resolution, which...
We present PolyBuilding, a fully end-to-end polygon Transformer for buil...
Training a large-scale deep neural network in a large-scale dataset is
c...
The ability to decompose complex natural scenes into meaningful
object-c...
Recent generative models show impressive results in photo-realistic imag...
Efficient and effective exploration in continuous space is a central pro...
Unit tests are widely used to check source code quality, but they can be...
Data cleaning, architecture, and loss function design are important fact...
Open-world instance segmentation (OWIS) aims to segment class-agnostic
i...
We present a conceptually simple, flexible, and universal visual percept...
Integrating logical reasoning and machine learning by approximating logi...
Learning robust feature representation from large-scale noisy faces stan...
Large-scale deployment of autonomous vehicles has been continually delay...
Simulating urban morphology with location attributes is a challenging ta...
Light-sheet fluorescence microscopy (LSFM) is a cutting-edge volumetric
...
In presence of spatial heterogeneity, models applied to geographic data ...
This paper introduces the recent work of Nebula Graph, an open-source,
d...
Facial semantic guidance (facial landmarks, facial parsing maps, facial
...
Pedestrian dead reckoning is a challenging task due to the low-cost iner...
Ultrasonography is an important routine examination for breast cancer
di...
The vision-based grasp detection method is an important research directi...
In this paper we present a Fourier feature based deep domain decompositi...
One essential task for autonomous driving is to encode the information o...
Recommender systems have been successfully used in many domains with the...
Purpose: To introduce a dual-domain reconstruction network with V-Net an...
It is a challenging task to learn discriminative representation from ima...
It is a challenging task to learn rich and multi-scale spatiotemporal
se...
Knowledge graph embedding (KGE) has drawn great attention due to its
pot...
Visual place recognition (VPR) is a challenging task with the unbalance
...