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Found 7 papers, 2 papers with code
Multi-modal News Understanding with Professionally Labelled Videos (ReutersViLNews)
Towards a solution for designing this ability in algorithms, we present a large-scale analysis on an in-house dataset collected by the Reuters News Agency, called Reuters Video-Language News (ReutersViLNews) dataset which focuses on high-level video-language understanding with an emphasis on long-form news.
Implicit and Explicit Commonsense for Multi-sentence Video Captioning
We show that our commonsense knowledge enhanced approach produces significant improvements on this task (up to 57% in METEOR and 8. 5% in CIDEr), as well as the state-of-the-art result on more traditional video captioning in the ActivityNet Captions dataset [29].
An Improved Attention for Visual Question Answering
We also propose multimodal fusion module to combine both visual and textual information.
Visual Question Answering on 360° Images
We then study two different VQA models on VQA 360, including one conventional model that takes an equirectangular image (with intrinsic distortion) as input and one dedicated model that first projects a 360 image onto cubemaps and subsequently aggregates the information from multiple spatial resolutions.
360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images
In this paper, our goal is to provide a standard dataset to facilitate the vision and machine learning communities in 360{\deg} domain.
Self-view Grounding Given a Narrated 360° Video
The negative log reconstruction loss of the reverse sentence (referred to as "irrelevant loss") is jointly minimized to encourage the reverse sentence to be different from the given sentence.
Agent-Centric Risk Assessment: Accident Anticipation and Risky Region Localization
For survival, a living agent must have the ability to assess risk (1) by temporally anticipating accidents before they occur, and (2) by spatially localizing risky regions in the environment to move away from threats.
