3 papers
cs.CV2026
Exploring Easy Boosts for Lidar Semantic Scene Completion
Tetiana Martyniuk, Jonathan Seele, Alexandre Boulch +3
This paper investigates "free lunch" strategies to boost the performance of lidar semantic scene completion (SSC) without requiring complex architectural redesigns. We first demons…
cs.CV2025
LiDPM: Rethinking Point Diffusion for Lidar Scene Completion
Tetiana Martyniuk, Gilles Puy, Alexandre Boulch +2
Training diffusion models that work directly on lidar points at the scale of outdoor scenes is challenging due to the difficulty of generating fine-grained details from white noise…
cs.CV2019
DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
Orest Kupyn, Tetiana Martyniuk, Junru Wu +1
We present a new end-to-end generative adversarial network (GAN) for single image motion deblurring, named DeblurGAN-v2, which considerably boosts state-of-the-art deblurring effic…