works on

From the 1 of 6 linked papers with an AI index.

activity
20242026
collaborators

6 papers

cs.CV2026

EquiFusion: Kinematics-Agnostic Human Motion Prediction via Equivariant Latent Diffusion

Cecilia Curreli, Florian Hofherr, Dominik Muhle +3

EquiFusion is a latent diffusion model for 3D human motion prediction that does not rely on fixed skeleton kinematics, allowing it to generalize across datasets and handle partial…

cs.CV2026

Benchmarking Single-Step Inpainting Methods for Multi-Object 3D Gaussian Splatting Scenes

Finn Dröge, Cecilia Curreli, Abhishek Saroha +1

The tasks of object removal and inpainting 3D Gaussian Splatting (3DGS) scenes face challenges such as 3D consistency across camera views. In comparing 2D inpainters and their suit…

cs.CV2025

Nonisotropic Gaussian Diffusion for Realistic 3D Human Motion Prediction

Cecilia Curreli, Dominik Muhle, Abhishek Saroha +3

Probabilistic human motion prediction aims to forecast multiple possible future movements from past observations. While current approaches report high diversity and realism, they o…

cs.LG2025

Prototype Augmented Hypernetworks for Continual Learning

Neil De La Fuente, Maria Pilligua, Daniel Vidal +4

Continual learning (CL) aims to learn a sequence of tasks without forgetting prior knowledge, but gradient updates for a new task often overwrite the weights learned earlier, causi…

cs.CV2025

ZDySS -- Zero-Shot Dynamic Scene Stylization using Gaussian Splatting

Abhishek Saroha, Florian Hofherr, Mariia Gladkova +3

Stylizing a dynamic scene based on an exemplar image is critical for various real-world applications, including gaming, filmmaking, and augmented and virtual reality. However, achi…

cs.CV2024

Gaussian Splatting in Style

Abhishek Saroha, Mariia Gladkova, Cecilia Curreli +3

3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple vie…