In recommendation systems (RS), user behavior data is observational rath...
Data-free knowledge distillation (DFKD) aims to obtain a lightweight stu...
Graph Neural Networks (GNNs) have emerged as the de facto standard for
r...
Multi-Teacher knowledge distillation provides students with additional
s...
Recent years have witnessed significant progress in developing efficient...
Text-driven 3D scene generation is widely applicable to video gaming, fi...
Neural implicit fields are powerful for representing 3D scenes and gener...
In this paper, we study the Robust optimization for
sequence Networked s...
As a powerful representation of 3D scenes, the neural radiance field (Ne...
Although diffusion model has shown great potential for generating higher...
Graph neural networks (GNNs) have become one of the most popular researc...
We propose a Few-shot Dynamic Neural Radiance Field (FDNeRF), the first
...
Knowledge graph embedding (KGE) has been intensively investigated for li...
In this paper, we are concerned with the numerical solution for the
two-...
In this work, based on the complete Bernstein function, we propose a
gen...
Existing knowledge distillation methods on graph neural networks (GNNs) ...
Knowledge distillation aims to compress a powerful yet cumbersome teache...
Knowledge distillation aims to enhance the performance of a lightweight
...
Localizing keypoints of an object is a basic visual problem. However,
su...
Knowledge distillation is initially introduced to utilize additional
sup...
Knowledge distillation has recently become a popular technique to improv...
We present CLIP-NeRF, a multi-modal 3D object manipulation method for ne...
Knowledge distillation is a generalized logits matching technique for mo...
Knowledge Distillation (KD) aims at transferring knowledge from a larger...
Despite recent breakthroughs in deep learning methods for image lighting...
Heatmap-based methods dominate in the field of human pose estimation by
...
Face image manipulation via three-dimensional guidance has been widely
a...
Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to...
Sampling strategies have been widely applied in many recommendation syst...
Recommendation from implicit feedback is a highly challenging task due t...
Recommendation system plays an important role in online web applications...
Remarkable progress has been made in 3D human pose estimation from a
mon...
This paper investigates the task of 2D human whole-body pose estimation,...
It has been a significant challenge to portray intraclass disparity prec...
Current facial expression recognition methods fail to simultaneously cop...
Modeling complex spatial and temporal correlations in the correlated tim...
Recommendation from implicit feedback is a highly challenging task due t...
Distillation is an effective knowledge-transfer technique that uses pred...
Graph Neural Networks (GNNs), which generalize deep neural networks to
g...
Given the intractability of large scale HIN, network embedding which lea...
Multi-person pose estimation is fundamental to many computer vision task...
Multimodal wearable sensor data classification plays an important role i...
Sales forecast is an essential task in E-commerce and has a crucial impa...
Existing works for extracting navigation objects from webpages focus on
...
Humans develop a common sense of style compatibility between items based...
Blog is becoming an increasingly popular media for information publishin...