Fabricating and designing 3D garments has become extremely demanding wit...
Panoramic image enables deeper understanding and more holistic perceptio...
Talking head generation aims to generate faces that maintain the identit...
Radiance field is an effective representation of 3D scenes, which has be...
Recommender systems have been demonstrated to be effective to meet user'...
In this paper, we present a novel and effective framework, named 4K-NeRF...
Approximating radiance fields with volumetric grids is one of promising
...
While action anticipation has garnered a lot of research interest recent...
As there is a growing interest in utilizing data across multiple resourc...
Crime prediction is crucial for public safety and resource optimization,...
Many previous studies aim to augment collaborative filtering with deep n...
Accurate forecasting of citywide traffic flow has been playing critical ...
Capturing users' precise preferences is of great importance in various
r...
Accurate user and item embedding learning is crucial for modern recommen...
Session-based recommendation plays a central role in a wide spectrum of
...
Social recommendation task aims to predict users' preferences over items...
Modern recommender systems often embed users and items into low-dimensio...
In recent years, researchers attempt to utilize online social informatio...
Vertical federated learning (VFL) is an effective paradigm of training t...
In this paper, we propose a novel video super-resolution method that aim...
In this paper, we present Fedlearn-Algo, an open-source privacy preservi...
To promote the developments of object detection, tracking and counting
a...
It is challenging to train a robust object detector when annotated data ...
We investigate large-scale latent variable models (LVMs) for neural stor...
Large-scale pretrained language models have shown thrilling generation
c...
Pig counting is a crucial task for large-scale pig farming, which is usu...
Fraud detection is extremely critical for e-commerce business. It is the...
This paper proposes a space-time multi-scale attention network (STANet) ...
Graph representation learning is to learn universal node representations...
Heatmap regression has became one of the mainstream approaches to locali...
In this paper, we present a unified, end-to-end trainable spatiotemporal...
Current state-of-the-art object objectors are fine-tuned from the
off-th...