activity
20222024
most citedLaTeRF: Label and Text Driven Object Radiance Fields

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting

Umangi Jain, Ashkan Mirzaei, Igor Gilitschenski

We introduce GaussianCut, a new method for interactive multiview segmentation of scenes represented as 3D Gaussians. Our approach allows for selecting the objects to be segmented b…

cs.CV20241 cited

L4GM: Large 4D Gaussian Reconstruction Model

Jiawei Ren, Kevin Xie, Ashkan Mirzaei +8

We present L4GM, the first 4D Large Reconstruction Model that produces animated objects from a single-view video input -- in a single feed-forward pass that takes only a second. Ke…

cs.CV2024

RefFusion: Reference Adapted Diffusion Models for 3D Scene Inpainting

Ashkan Mirzaei, Riccardo De Lutio, Seung Wook Kim +5

Neural reconstruction approaches are rapidly emerging as the preferred representation for 3D scenes, but their limited editability is still posing a challenge. In this work, we pro…

cs.CV2023

CAMM: Building Category-Agnostic and Animatable 3D Models from Monocular Videos

Tianshu Kuai, Akash Karthikeyan, Yash Kant +2

Animating an object in 3D often requires an articulated structure, e.g. a kinematic chain or skeleton of the manipulated object with proper skinning weights, to obtain smooth movem…

cs.CV20221 cited

LaTeRF: Label and Text Driven Object Radiance Fields

Ashkan Mirzaei, Yash Kant, Jonathan Kelly +1

Obtaining 3D object representations is important for creating photo-realistic simulations and for collecting AR and VR assets. Neural fields have shown their effectiveness in learn…