Signed graphs are well-suited for modeling social networks as they captu...
Modeling and predicting the performance of students in collaborative lea...
One key communication block in 5G and 6G radios is the active phased arr...
Text-to-image diffusion models can create stunning images from natural
l...
Attention-based vision models, such as Vision Transformer (ViT) and its
...
Existing 3D-from-2D generators are typically designed for well-curated
s...
Building animatable and editable models of clothed humans from raw 3D sc...
We propose a novel approach for unsupervised 3D animation of non-rigid
d...
With the success of Vision Transformers (ViTs) in computer vision tasks,...
Recent efforts in Neural Rendering Fields (NeRF) have shown impressive
r...
Recent works on diffusion models have demonstrated a strong capability f...
There has been a recent explosion of impressive generative models that c...
Recently, sparse training has emerged as a promising paradigm for effici...
Processing-in-memory (PIM), an increasingly studied neuromorphic hardwar...
Existing self-supervised monocular depth estimation methods can get rid ...
Creating and editing the shape and color of 3D objects require tremendou...
Graph-based anomaly detection is becoming prevalent due to the powerful
...
Diffusion probabilistic models (DPMs) have become a popular approach to
...
Vision Transformers (ViT) have shown rapid progress in computer vision t...
Multimodal data collected from the real world are often imperfect due to...
Recent research explosion on Neural Radiance Field (NeRF) shows the
enco...
Most methods for conditional video synthesis use a single modality as th...
Neural network quantization is a promising compression technique to redu...
Camera, and associated with its objects within the field of view,
locali...
Graph-based Anomaly Detection (GAD) is becoming prevalent due to the pow...
Human motion retargeting aims to transfer the motion of one person in a
...
Image and video synthesis are closely related areas aiming at generating...
We propose novel motion representations for animating articulated object...
A common assumption in multimodal learning is the completeness of traini...
Generative Adversarial Networks (GANs) have achieved huge success in
gen...
In deep model compression, the recent finding "Lottery Ticket Hypothesis...
In this paper, we propose a generic neural-based hair rendering pipeline...
In this paper, we tackle the problem of human motion transfer, where we
...
Extracting the governing stochastic differential equation model from elu...
A cryptocurrency is a decentralized digital currency that is designed fo...
Current systems used by medical institutions for the management and tran...
A lot of research has been focused on secure outsourcing of biometric
id...
Designing the structure of neural networks is considered one of the most...
In this paper, we propose Factorized Adversarial Networks (FAN) to solve...
Automatic and accurate Gleason grading of histopathology tissue slides i...
Cloud computing has changed the way enterprises store, access and share ...
The proliferation of online biometric authentication has necessitated
se...