Graph Neural Networks (GNNs) have gained momentum in graph representation learning
and boosted the state of the art in a variety of areas, such as data mining (eg, social network …

Limited training data is a long-standing problem for video emotion analysis (VEA). Existing
works leverage the power of large-scale image datasets for transferring while failing to …

Transformer-based approaches have achieved promising performance in image restoration
tasks given their ability to model long-range dependencies which is crucial for recovering …

Video prediction is a challenging task due to its nature of uncertainty especially for
forecasting a long period. To model the temporal dynamics advanced methods benefit from …

Camouflaged vision perception is an important vision task with numerous practical
applications. Due to the expensive collection and labeling costs this community struggles …

Reconstructing 3D human mesh from a single RGB image is a challenging task due to the
inherent depth ambiguity. Researchers commonly use convolutional neural networks to …

In the current digital era, large-scale Artificial Intelligence (AI) models have fundamentally
changed the landscape of the AI field. These models excel at extracting complex patterns …

Recovering 3D human mesh from videos has recently made significant progress. However,
most of the existing methods focus on the temporal consistency of videos, while ignoring the …

We present HumanNeRF-SE a simple yet effective method that synthesizes diverse novel
pose images with simple input. Previous HumanNeRF works require a large number of …

3D human pose and shape estimation from a single RGB image is an appealing yet
challenging task. Due to the graph-like nature of human parametric models, a growing …