activity
20242026
collaborators

36 papers

cs.CV2026

SynCity 3000: Bootstrapping Scene-Scale 3D Diffusion

Paul Engstler, Iro Laina, Christian Rupprecht +1

We present SynCity 3000, a framework for generating 3D scenes that are globally coherent while enabling fine-grained layout control. Building on the ability of current image-to-3D…

cs.CV2026

Syn4D: A Multiview Synthetic 4D Dataset

Zeren Jiang, Yushi Lan, Yihang Luo +8

Dense 3D reconstruction and tracking of dynamic scenes from monocular video remains an important open challenge in computer vision. Progress in this area has been constrained by th…

cs.CV2026

PhysiFormer: Learning to Simulate Mechanics in World Space

Yiming Chen, Yushi Lan, Andrea Vedaldi

We present PhysiFormer, a diffusion transformer for physically-plausible 3D object motion. Unlike video world models that operate in view-dependent pixel space, PhysiFormer represe…

cs.CV2026

Instruct-Particulate: Scaling Feed-Forward 3D Object Articulation with Kinematic Control

Ruining Li, Yuxin Yao, Matt Zhou +5

Reconstructing articulated 3D objects is important for animation, gaming, and robotic simulations. Recent neural networks can estimate the articulated structure of 3D objects, but…

cs.CV2026

LagerNVS: Latent Geometry for Fully Neural Real-time Novel View Synthesis

Stanislaw Szymanowicz, Minghao Chen, Jianyuan Wang +2

Recent work has shown that neural networks can perform 3D tasks such as Novel View Synthesis (NVS) without explicit 3D reconstruction. Even so, we argue that strong 3D inductive bi…

cs.CV2026

What Happens Next? Anticipating Future Motion by Generating Point Trajectories

Gabrijel Boduljak, Laurynas Karazija, Iro Laina +2

We consider the problem of forecasting motion from a single image, i.e., predicting how objects in the world are likely to move, without the ability to observe other parameters suc…