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20232026
most citedMoVideo: Motion-Aware Video Generation with Diffusion Models

2 citations · 4 across the 12 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion

Zhenggang Tang, Yuehao Wang, Yuchen Fan +9

Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a scene layout or to generate…

cs.CV2025

Shoot-Bounce-3D: Single-Shot Occlusion-Aware 3D from Lidar by Decomposing Two-Bounce Light

Tzofi Klinghoffer, Siddharth Somasundaram, Xiaoyu Xiang +5

3D scene reconstruction from a single measurement is challenging, especially in the presence of occluded regions and specular materials, such as mirrors. We address these challenge…

cs.CV2025

WorldGen: From Text to Traversable and Interactive 3D Worlds

Dilin Wang, Hyunyoung Jung, Tom Monnier +22

We introduce WorldGen, a system that enables the automatic creation of large-scale, interactive 3D worlds directly from text prompts. Our approach transforms natural language descr…

cs.CV2025

Make-A-Texture: Fast Shape-Aware Texture Generation in 3 Seconds

Xiaoyu Xiang, Liat Sless Gorelik, Yuchen Fan +5

We present Make-A-Texture, a new framework that efficiently synthesizes high-resolution texture maps from textual prompts for given 3D geometries. Our approach progressively genera…

cs.CV2024

MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds

Zhenggang Tang, Yuchen Fan, Dilin Wang +4

Recent sparse multi-view scene reconstruction advances like DUSt3R and MASt3R no longer require camera calibration and camera pose estimation. However, they only process a pair of…

cs.CV2024

3D Mesh Editing using Masked LRMs

Will Gao, Dilin Wang, Yuchen Fan +6

We present a novel approach to shape editing, building on recent progress in 3D reconstruction from multi-view images. We formulate shape editing as a conditional reconstruction pr…

cs.CV2024

WaSt-3D: Wasserstein-2 Distance for Scene-to-Scene Stylization on 3D Gaussians

Dmytro Kotovenko, Olga Grebenkova, Nikolaos Sarafianos +8

While style transfer techniques have been well-developed for 2D image stylization, the extension of these methods to 3D scenes remains relatively unexplored. Existing approaches de…

cs.CV2024

MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction

Shitao Tang, Jiacheng Chen, Dilin Wang +6

This paper presents a neural architecture MVDiffusion++ for 3D object reconstruction that synthesizes dense and high-resolution views of an object given one or a few images without…

cs.CV2023★ 1 cited

PlatoNeRF: 3D Reconstruction in Plato's Cave via Single-View Two-Bounce Lidar

Tzofi Klinghoffer, Xiaoyu Xiang, Siddharth Somasundaram +4

3D reconstruction from a single-view is challenging because of the ambiguity from monocular cues and lack of information about occluded regions. Neural radiance fields (NeRF), whil…

cs.CV2023★ 1 cited

Customizing 360-Degree Panoramas through Text-to-Image Diffusion Models

Hai Wang, Xiaoyu Xiang, Yuchen Fan +1

Personalized text-to-image (T2I) synthesis based on diffusion models has attracted significant attention in recent research. However, existing methods primarily concentrate on cust…

cs.CV2023★ 2 cited

MoVideo: Motion-Aware Video Generation with Diffusion Models

Jingyun Liang, Yuchen Fan, Kai Zhang +3

While recent years have witnessed great progress on using diffusion models for video generation, most of them are simple extensions of image generation frameworks, which fail to ex…