Recent works reveal that adversarial augmentation benefits the generaliz...
Vision Transformers (ViTs) have recently become the state-of-the-art acr...
Recently, a number of new Semi-Supervised Learning methods have emerged....
Current deep neural networks (DNNs) are vulnerable to adversarial attack...
In this paper, we provide a deep analysis of temporal modeling for actio...
Single-particle cryo-electron microscopy (cryo-EM) has become one of the...
We propose a new perspective on video understanding by casting the video...
Vision transformer (ViT) has recently showed its strong capability in
ac...
Multi-modal learning, which focuses on utilizing various modalities to
i...
The recently developed vision transformer (ViT) has achieved promising
r...
Machine learning (ML) models that learn and predict properties of comput...
In recent years, a number of approaches based on 2D CNNs and 3D CNNs hav...
Current state-of-the-art models for video action recognition are mostly ...
It is known that deep neural networks (DNNs) could be vulnerable to
adve...
Objects are entities we act upon, where the functionality of an object i...
It is widely known that convolutional neural networks (CNNs) are vulnera...
We propose a new method for exploiting sparsity in convolutional kernels...
In this paper, we propose a novel Convolutional Neural Network (CNN)
arc...
We present the Moments in Time Dataset, a large-scale human-annotated
co...