3 citations · 8 across the 12 of their papers we have counts for
12 papers
AssetGen: Deployable 3D Asset Generation at Interactive Speed
Dilin Wang, Xiaoyu Xiang, Kihyuk Sohn +14
While 3D generation is progressing rapidly, recent work has often focused on obtaining high-resolution assets, leaving user experience and deployability as afterthoughts. We presen…
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…
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…
Real Deep Research for AI, Robotics and Beyond
Xueyan Zou, Jianglong Ye, Hao Zhang +7
With the rapid growth of research in AI and robotics now producing over 10,000 papers annually it has become increasingly difficult for researchers to stay up to date. Fast evolvin…
A Survey on Text-Driven 360-Degree Panorama Generation
Hai Wang, Xiaoyu Xiang, Weihao Xia +1
The advent of text-driven 360-degree panorama generation, enabling the synthesis of 360-degree panoramic images directly from textual descriptions, marks a transformative advanceme…
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…
UnSAMFlow: Unsupervised Optical Flow Guided by Segment Anything Model
Shuai Yuan, Lei Luo, Zhuo Hui +4
Traditional unsupervised optical flow methods are vulnerable to occlusions and motion boundaries due to lack of object-level information. Therefore, we propose UnSAMFlow, an unsupe…
Garment3DGen: 3D Garment Stylization and Texture Generation
Nikolaos Sarafianos, Tuur Stuyck, Xiaoyu Xiang +3
We introduce Garment3DGen a new method to synthesize 3D garment assets from a base mesh given a single input image as guidance. Our proposed approach allows users to generate 3D te…
CAD: Photorealistic 3D Generation via Adversarial Distillation
Ziyu Wan, Despoina Paschalidou, Ian Huang +5
The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects. Most of the…
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…
Training Neural Networks on RAW and HDR Images for Restoration Tasks
Andrew Yanzhe Ke, Lei Luo, Xiaoyu Xiang +4
The vast majority of standard image and video content available online is represented in display-encoded color spaces, in which pixel values are conveniently scaled to a limited ra…
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…