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Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos
TLDR
A deep neural framework is proposed, termed conversational memory network, which leverages contextual information from the conversation history to recognize utterance-level emotions in dyadic conversational videos.
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection
TLDR
Interactive COnversational memory Network (ICON), a multi-modal emotion detection framework that extracts multimodal features from conversational videos and hierarchically models the self- and inter-speaker emotional influences into global memories to aid in predicting the emotional orientation of utterance-videos.
CASCADE: Contextual Sarcasm Detection in Online Discussion Forums
TLDR
This paper proposes a ContextuAl SarCasm DEtector (CASCADE), which adopts a hybrid approach of both content- and context-driven modeling for sarcasm detection in online social media discussions.
A Survey on Bitrate Adaptation Schemes for Streaming Media Over HTTP
TLDR
This survey provides an overview of the different methods proposed over the last several years of bitrate adaptation algorithms for HTTP adaptive streaming, leaving it to system builders to innovate and implement their own method.
Canopy transpiration and water fluxes in the xylem of the trunk of Larix and Picea trees — a comparison of xylem flow, porometer and cuvette measurements
TLDR
Investigation of the daily water balance of intact, naturally growing, adult Larix and Picea trees without major injury found that plant water status recovers with the decrease of transpiration and the refilling of the water storage sites.
SDNDASH: Improving QoE of HTTP Adaptive Streaming Using Software Defined Networking
TLDR
A new software defined networking (SDN) based dynamic resource allocation and management architecture for HAS systems is proposed, which aims to alleviate scalability issues and improve the per-client QoE.
SCADDAR: an efficient randomized technique to reorganize continuous media blocks
TLDR
The SCADDAR approach is based on using a series of REMAP functions which can derive the location of a new block using only its original location as a basis and meets the objective to redistribute a minimum number of media blocks after disk scaling.
Viewable scene modeling for geospatial video search
TLDR
An estimation model of the viewable area of a scene for indexing and searching and reports on a prototype implementation of a novel approach for querying videos based on the notion that the geographical location of the captured scene in addition to the location of a camera can provide valuable information and may be used as a search criterion in many applications.
Towards Natural and Accurate Future Motion Prediction of Humans and Animals
TLDR
A hierarchical recurrent network structure is developed to simultaneously encodes local contexts of individual frames and global contexts of the sequence, which achieves more natural and accurate predictions over state-of-the-art methods.
The multi-rule partial sequenced route query
TLDR
It is proved that MRPSR is NP-hard and then three heuristic algorithms to search for near-optimal solutions for the MR PSR query are presented, which are remarkably reduced while the resulting route length is only slightly longer than the shortest route.
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