2 citations · 2 across the 4 of their papers we have counts for
4 papers
Learned Compression of Encoding Distributions
Mateen Ulhaq, Ivan V. Bajić
The entropy bottleneck introduced by Ballé et al. is a common component used in many learned compression models. It encodes a transformed latent representation using a static distr…
Scalable Human-Machine Point Cloud Compression
Mateen Ulhaq, Ivan V. Bajić
Due to the limited computational capabilities of edge devices, deep learning inference can be quite expensive. One remedy is to compress and transmit point cloud data over the netw…
Learned Point Cloud Compression for Classification
Mateen Ulhaq, Ivan V. Bajić
Deep learning is increasingly being used to perform machine vision tasks such as classification, object detection, and segmentation on 3D point cloud data. However, deep learning i…
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…