We propose a new simple approach for image compression: instead of storing the RGB
values for each pixel of an image, we store the weights of a neural network overfitted to the …

Most neural compression models are trained on large datasets of images or videos in order
to generalize to unseen data. Such generalization typically requires large and expressive …

Significant advances in video compression systems have been made in the past several
decades to satisfy the near-exponential growth of Internet-scale video traffic. From the …

Inferring the quality of streaming video applications is important for Internet service
providers, but the fact that most video streams are encrypted makes it difficult to do so. We …

Measuring Quality of Experience (QoE) and integrating these measurements into video
streaming algorithms is a multi-faceted problem that fundamentally requires the design of …

Video transcoding is the process of encoding an initial video sequence into multiple
sequences of different bitrates, resolutions, and video standards, so that it can be viewed on …

One of the challenges faced by many video providers is the heterogeneity of network
specifications, user requirements, and content compression performance. The universal …

Simple quality metrics such as PSNR are known to not correlate well with subjective quality
when tested across a wide spectrum of video content or quality regime. Recently, efforts …

Because of the increasing ease of video capture, many millions of consumers create and
upload large volumes of User-Generated-Content (UGC) videos to social and streaming …

Streaming video algorithms dynamically select between different versions of a video to
deliver the highest quality version that can be viewed without buffering over the client's …