69 citations · 367 across the 45 of their papers we have counts for
51 papers
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…
When Do Diffusion Models learn to Generate Multiple Objects?
Yujin Jeong, Arnas Uselis, Iro Laina +2
Text-to-image diffusion models achieve impressive visual fidelity, yet they remain unreliable in multi-object generation. Despite extensive empirical evidence of these failures, th…
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…
Do 3D Large Language Models Really Understand 3D Spatial Relationships?
Xianzheng Ma, Tao Sun, Shuai Chen +7
Recent 3D Large-Language Models (3D-LLMs) claim to understand 3D worlds, especially spatial relationships among objects. Yet, we find that simply fine-tuning a language model on te…
Mesh4D: 4D Mesh Reconstruction and Tracking from Monocular Video
Zeren Jiang, Chuanxia Zheng, Iro Laina +2
We propose Mesh4D, a feed-forward model for monocular 4D mesh reconstruction. Given a monocular video of a dynamic object, our model reconstructs the object's complete 3D shape and…
TRAVL: A Recipe for Making Video-Language Models Better Judges of Physics Implausibility
Saman Motamed, Minghao Chen, Luc Van Gool +1
Despite impressive visual fidelity, modern video generative models frequently produce sequences that violate intuitive physical laws, such as objects floating, teleporting, or morp…