118 citations · 204 across the 8 of their papers we have counts for
14 papers
Leveraging progressive model and overfitting for efficient learned image compression
Honglei Zhang, Francesco Cricri, Hamed Rezazadegan Tavakoli +2
Deep learning is overwhelmingly dominant in the field of computer vision and image/video processing for the last decade. However, for image and video compression, it lags behind th…
Image coding for machines: an end-to-end learned approach
Nam Le, Honglei Zhang, Francesco Cricri +2
Over recent years, deep learning-based computer vision systems have been applied to images at an ever-increasing pace, oftentimes representing the only type of consumption for thos…
Lossless Image Compression Using a Multi-Scale Progressive Statistical Model
Honglei Zhang, Francesco Cricri, Hamed R. Tavakoli +3
Lossless image compression is an important technique for image storage and transmission when information loss is not allowed. With the fast development of deep learning techniques,…
Learned Image Coding for Machines: A Content-Adaptive Approach
Nam Le, Honglei Zhang, Francesco Cricri +3
Today, according to the Cisco Annual Internet Report (2018-2023), the fastest-growing category of Internet traffic is machine-to-machine communication. In particular, machine-to-ma…
Efficient Adaptation of Neural Network Filter for Video Compression
Yat-Hong Lam, Alireza Zare, Francesco Cricri +2
We present an efficient finetuning methodology for neural-network filters which are applied as a postprocessing artifact-removal step in video coding pipelines. The fine-tuning is…
End-to-End Learning for Video Frame Compression with Self-Attention
Nannan Zou, Honglei Zhang, Francesco Cricri +5
One of the core components of conventional (i.e., non-learned) video codecs consists of predicting a frame from a previously-decoded frame, by leveraging temporal correlations. In…