9 citations · 9 across the 6 of their papers we have counts for
6 papers
Controllable 3D Placement of Objects with Scene-Aware Diffusion Models
Mohamed Omran, Dimitris Kalatzis, Jens Petersen +2
Image editing approaches have become more powerful and flexible with the advent of powerful text-conditioned generative models. However, placing objects in an environment with a pr…
Gaussian Splatting is an Effective Data Generator for 3D Object Detection
Farhad G. Zanjani, Davide Abati, Auke Wiggers +4
We investigate data augmentation for 3D object detection in autonomous driving. We utilize recent advancements in 3D reconstruction based on Gaussian Splatting for 3D object placem…
MobileNVC: Real-time 1080p Neural Video Compression on a Mobile Device
Ties van Rozendaal, Tushar Singhal, Hoang Le +10
Neural video codecs have recently become competitive with standard codecs such as HEVC in the low-delay setting. However, most neural codecs are large floating-point networks that…
Pulling back information geometry
Georgios Arvanitidis, Miguel González-Duque, Alison Pouplin +2
Latent space geometry has shown itself to provide a rich and rigorous framework for interacting with the latent variables of deep generative models. The existing theory, however, r…
Density estimation on smooth manifolds with normalizing flows
Dimitris Kalatzis, Johan Ziruo Ye, Alison Pouplin +2
We present a framework for learning probability distributions on topologically non-trivial manifolds, utilizing normalizing flows. Current methods focus on manifolds that are homeo…
Variational Autoencoders with Riemannian Brownian Motion Priors
Dimitris Kalatzis, David Eklund, Georgios Arvanitidis +1
Variational Autoencoders (VAEs) represent the given data in a low-dimensional latent space, which is generally assumed to be Euclidean. This assumption naturally leads to the commo…