Human beings experience life through a spectrum of modes such as vision, taste, hearing,
smell, and touch. These multiple modes are integrated for information processing in our …

As humans, we experience the world with all our senses or modalities (sound, sight, touch,
smell, and taste). We use these modalities, particularly sight and touch, to convey and …

Video action recognition needs to model any differences by subdividing the spatio-temporal
features to distinguish various actions. We propose rethinking spatio-temporal cross …

Multi-action video recognition is much more challenging due to the requirement to recognize
multiple actions co-occurring simultaneously or sequentially. Modeling multi-action relations …

Applications such as providing a preview of personal albums (eg, Google Photos) or
suggesting thematic collections based on user interests (eg, Pinterest) require a …

Image classification is a challenging problem and often suffers from the bottleneck of visual
features. With the ever-growing availability of multimedia data with the help of the Internet …

Although artificial intelligence (AI) has achieved many feats at a rapid pace, there still exist
open problems and fundamental shortcomings related to performance and resource …

Recently, two-stream networks with multi-modality inputs have shown to be of vital
importance for state-of-the-art video understanding. Previous deep systems typically employ …

Deep learning models are characterized by high complexity and low interpretability, which
are the payload for obtaining precise results in difficult tasks such as image understanding …

Videos captured in low light conditions can be processed in order to identify an activity being
performed in the video. The processing may use both the video and audio streams for …