Zobrazeno 1 - 10
of 565
pro vyhledávání: '"Kaufman, Arie"'
Autor:
Xie, Desai, Xu, Zhan, Hong, Yicong, Tan, Hao, Liu, Difan, Liu, Feng, Kaufman, Arie, Zhou, Yang
Current frontier video diffusion models have demonstrated remarkable results at generating high-quality videos. However, they can only generate short video clips, normally around 10 seconds or 240 frames, due to computation limitations during trainin
Externí odkaz:
http://arxiv.org/abs/2410.08151
Autor:
Xie, Desai, Bi, Sai, Shu, Zhixin, Zhang, Kai, Xu, Zexiang, Zhou, Yi, Pirk, Sören, Kaufman, Arie, Sun, Xin, Tan, Hao
We present LRM-Zero, a Large Reconstruction Model (LRM) trained entirely on synthesized 3D data, achieving high-quality sparse-view 3D reconstruction. The core of LRM-Zero is our procedural 3D dataset, Zeroverse, which is automatically synthesized fr
Externí odkaz:
http://arxiv.org/abs/2406.09371
Autor:
Xie, Desai, Li, Jiahao, Tan, Hao, Sun, Xin, Shu, Zhixin, Zhou, Yi, Bi, Sai, Pirk, Sören, Kaufman, Arie E.
Multi-view diffusion models, obtained by applying Supervised Finetuning (SFT) to text-to-image diffusion models, have driven recent breakthroughs in text-to-3D research. However, due to the limited size and quality of existing 3D datasets, they still
Externí odkaz:
http://arxiv.org/abs/2312.13980
While developing new unsupervised domain translation methods for endoscopy videos, it is typical to start with approaches that initially work for individual frames without temporal consistency. Once an individual-frame model has been finalized, addit
Externí odkaz:
http://arxiv.org/abs/2310.00868
We present Submerse, an end-to-end framework for visualizing flooding scenarios on large and immersive display ecologies. Specifically, we reconstruct a surface mesh from input flood simulation data and generate a to-scale 3D virtual scene by incorpo
Externí odkaz:
http://arxiv.org/abs/2304.06872
Automated analysis of optical colonoscopy (OC) video frames (to assist endoscopists during OC) is challenging due to variations in color, lighting, texture, and specular reflections. Previous methods either remove some of these variations via preproc
Externí odkaz:
http://arxiv.org/abs/2206.14951
The growing complexity of spatial and structural information in 3D data makes data inspection and visualization a challenging task. We describe a method to create a planar embedding of 3D treelike structures using their skeleton representations. Our
Externí odkaz:
http://arxiv.org/abs/2202.10551
Autor:
Boorboor, Saeed, Mathew, Shawn, Ananth, Mala, Talmage, David, Role, Lorna W., Kaufman, Arie E.
Recent advances in high-resolution microscopy have allowed scientists to better understand the underlying brain connectivity. However, due to the limitation that biological specimens can only be imaged at a single timepoint, studying changes to neura
Externí odkaz:
http://arxiv.org/abs/2202.01115
Significant work has been done towards deep learning (DL) models for automatic lung and lesion segmentation and classification of COVID-19 on chest CT data. However, comprehensive visualization systems focused on supporting the dual visual+DL diagnos
Externí odkaz:
http://arxiv.org/abs/2108.03799
Haustral folds are colon wall protrusions implicated for high polyp miss rate during optical colonoscopy procedures. If segmented accurately, haustral folds can allow for better estimation of missed surface and can also serve as valuable landmarks fo
Externí odkaz:
http://arxiv.org/abs/2106.12522