161 citations · 266 across the 9 of their papers we have counts for
18 papers
Learned Disentangled Latent Representations for Scalable Image Coding for Humans and Machines
Ezgi Ozyilkan, Mateen Ulhaq, Hyomin Choi +1
As an increasing amount of image and video content will be analyzed by machines, there is demand for a new codec paradigm that is capable of compressing visual input primarily for…
Frequency-aware Learned Image Compression for Quality Scalability
Hyomin Choi, Fabien Racape, Shahab Hamidi-Rad +2
Spatial frequency analysis and transforms serve a central role in most engineered image and video lossy codecs, but are rarely employed in neural network (NN)-based approaches. We…
Scalable Video Coding for Humans and Machines
Hyomin Choi, Ivan V. Bajić
Video content is watched not only by humans, but increasingly also by machines. For example, machine learning models analyze surveillance video for security and traffic monitoring,…
Joint Image Compression and Denoising via Latent-Space Scalability
Saeed Ranjbar Alvar, Mateen Ulhaq, Hyomin Choi +1
When it comes to image compression in digital cameras, denoising is traditionally performed prior to compression. However, there are applications where image noise may be necessary…
SFU-HW-Tracks-v1: Object Tracking Dataset on Raw Video Sequences
Takehiro Tanaka, Hyomin Choi, Ivan V. Bajić
We present a dataset that contains object annotations with unique object identities (IDs) for the High Efficiency Video Coding (HEVC) v1 Common Test Conditions (CTC) sequences. Gro…
Scalable Image Coding for Humans and Machines
Hyomin Choi, Ivan V. Bajic
At present, and increasingly so in the future, much of the captured visual content will not be seen by humans. Instead, it will be used for automated machine vision analytics and m…