5 citations · 14 across the 8 of their papers we have counts for
6 papers · 1 filter
Differentiable bit-rate estimation for neural-based video codec enhancement
Amir Said, Manish Kumar Singh, Reza Pourreza
Neural networks (NN) can improve standard video compression by pre- and post-processing the encoded video. For optimal NN training, the standard codec needs to be replaced with a c…
Optimized learned entropy coding parameters for practical neural-based image and video compression
Amir Said, Reza Pourreza, Hoang Le
Neural-based image and video codecs are significantly more power-efficient when weights and activations are quantized to low-precision integers. While there are general-purpose tec…
Boosting neural video codecs by exploiting hierarchical redundancy
Reza Pourreza, Hoang Le, Amir Said +2
In video compression, coding efficiency is improved by reusing pixels from previously decoded frames via motion and residual compensation. We define two levels of hierarchical redu…
Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set
Ties van Rozendaal, Johann Brehmer, Yunfan Zhang +3
We introduce a video compression algorithm based on instance-adaptive learning. On each video sequence to be transmitted, we finetune a pretrained compression model. The optimal pa…
Extending Neural P-frame Codecs for B-frame Coding
Reza Pourreza, Taco S Cohen
While most neural video codecs address P-frame coding (predicting each frame from past ones), in this paper we address B-frame compression (predicting frames using both past and fu…
Adversarial Distortion for Learned Video Compression
Vijay Veerabadran, Reza Pourreza, Amirhossein Habibian +1
In this paper, we present a novel adversarial lossy video compression model. At extremely low bit-rates, standard video coding schemes suffer from unpleasant reconstruction artifac…