Related papers: Adaptive Video Streaming with AI-Based Optimizatio…
The quality of the video stream is key to neural network-based video analytics. However, low-quality video is inevitably collected by existing surveillance systems because of poor quality cameras or over-compressed/pruned video streaming…
Adapting video data rate during streaming can effectively reduce the risk of playback interruptions caused by channel throughput fluctuations. The variations in rate, however, also introduce video quality fluctuations and thus potentially…
Lossy compression and rate-adaptive streaming are a mainstay in traditional video steams. However, a new class of neuromorphic ``event'' sensors records video with asynchronous pixel samples rather than image frames. These sensors are…
In this study, we present a meta-learning model to adapt the predictions of the network's capacity between viewers who participate in a live video streaming event. We propose the MELANIE model, where an event is formulated as a Markov…
Adaptive video streaming relies on the construction of efficient bitrate ladders to deliver the best possible visual quality to viewers under bandwidth constraints. The traditional method of content dependent bitrate ladder selection…
Video streaming, in various forms of video on demand (VOD), live, and 360 degree streaming, has grown dramatically during the past few years. In comparison to traditional cable broadcasters whose contents can only be watched on TVs, video…
Dynamic Adaptive Streaming over HTTP (DASH) has emerged as an increasingly popular paradigm for video streaming [13], in which a video is segmented into many chunks delivered to users by HTTP request/response over Transmission Control…
Vehicular communication has become a reality guided by various applications. Among those, high video quality delivery with low latency constraints required by real-time applications constitutes a very challenging task. By dint of its…
Devising intelligent agents able to live in an environment and learn by observing the surroundings is a longstanding goal of Artificial Intelligence. From a bare Machine Learning perspective, challenges arise when the agent is prevented…
Networks are a natural representation of complex systems across the sciences, and higher-order dependencies are central to the understanding and modeling of these systems. However, in many practical applications such as online social…
In today's Internet, video is the most dominant application and in addition to this, wireless networks such as WiFi, Cellular, and Bluetooth have become ubiquitous. Hence, most of the Internet traffic is video over wireless nodes. There is…
AI Video Assistant emerges as a new paradigm for Real-time Communication (RTC), where one peer is a Multimodal Large Language Model (MLLM) deployed in the cloud. This makes interaction between humans and AI more intuitive, akin to chatting…
The rapid adoption of QUIC as a transport protocol has transformed content delivery by reducing latency, enhancing congestion control (CC), and enabling more efficient multiplexing. With the advent of 5G networks, which support ultra-low…
This survey presents the evolution of live media streaming and the technological developments behind today's IP-based low-latency live streaming systems. Live streaming primarily involves capturing, encoding, packaging and delivering…
Dynamic Adaptive Streaming over HTTP (DASH) has demonstrated to be an emerging and promising multimedia streaming technique, owing to its capability of dealing with the variability of networks. Rate adaptation mechanism, a challenging and…
While edge video caching has great potential to decrease the core network traffic as well as the users' experienced latency, it is often challenging to exploit the caches in current client-driven video streaming solutions due to two key…
Internet video delivery has undergone a tremendous explosion of growth over the past few years. However, the quality of video delivery system greatly depends on the Internet bandwidth. Deep Neural Networks (DNNs) are utilized to improve the…
Recognizing the surrounding environment at low latency is critical in autonomous driving. In real-time environment, surrounding environment changes when processing is over. Current detection models are incapable of dealing with changes in…
Dynamic adaptive streaming over HTTP provides the work of most multimedia services, however, the nature of this technology further complicates the assessment of the QoE (Quality of Experience). In this paper, the influence of various…
Video streaming services strive to support high-quality videos at higher resolutions and frame rates to improve the quality of experience (QoE). However, high-quality videos consume considerable amounts of energy on mobile devices. This…