Realistic object interactions are crucial for creating immersive virtual experiences, yet
synthesizing realistic 3D object dynamics in response to novel interactions remains a …

Existing dynamic scene generation methods mostly rely on distilling knowledge from pre-
trained 3D generative models, which are typically fine-tuned on synthetic object datasets. As …

Accurate reconstruction of complex dynamic scenes from just a single viewpoint continues to
be a challenging task in computer vision. Current dynamic novel view synthesis methods …

Gaussian splatting has become a popular representation for novel-view synthesis, exhibiting
clear strengths in efficiency, photometric quality, and compositional edibility. Following its …

Recently, breakthroughs in video modeling have allowed for controllable camera trajectories
in generated videos. However, these methods cannot be directly applied to user-provided …

In this paper, we propose MoDGS, a new pipeline to render novel views of dy namic scenes
from a casually captured monocular video. Previous monocular dynamic NeRF or Gaussian …

Neural rendering has demonstrated remarkable success in dynamic scene reconstruction.
Thanks to the expressiveness of neural representations prior works can accurately capture …

Dynamic reconstruction and spatiotemporal novel-view synthesis of non-rigidly deforming
scenes recently gained increased attention. While existing work achieves impressive quality …

The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes
the refereed proceedings of the 18th European Conference on Computer Vision, ECCV …

Synthesizing photo-realistic visual observations from an ego vehicle's driving trajectory is a
critical step towards scalable training of self-driving models. Reconstruction-based methods …