Abstract Recently, 3D Gaussian splatting (3D-GS) has gained popularity in novel-view
scene synthesis. It addresses the challenges of lengthy training times and slow rendering …

Federated learning (FL) is a machine learning setting where many clients (eg, mobile
devices or whole organizations) collaboratively train a model under the orchestration of a …

We review a class of methods that can be collected under the name nonlinear transform
coding (NTC), which over the past few years have become competitive with the best linear …

Abstract Implicit Neural Representations (INR) or neural fields have emerged as a popular
framework to encode multimedia signals such as images and radiance fields while retaining …

We consider the problem of training a $ d $ dimensional model with distributed differential
privacy (DP) where secure aggregation (SecAgg) is used to ensure that the server only sees …

Abstract The emergence of Neural Radiance Fields (NeRF) has greatly impacted 3D scene
modeling and novel-view synthesis. As a kind of visual media for 3D scene representation …

Implicit neural representations (INRs) have emerged as a promising approach for video
storage and processing showing remarkable versatility across various video tasks. However …

Abstract Implicit Neural Representations (INR) have recently shown to be powerful tool for
high-quality video compression. However, existing works are limiting as they do not explicitly …

In this paper, we compress convolutional neural network (CNN) weights post-training via
transform quantization. Previous CNN quantization techniques tend to ignore the joint …

Encoding videos as neural networks is a recently proposed approach that allows new forms
of video processing. However, traditional techniques still outperform such neural video …