no code implementations • 26 Sep 2024 • Zhenghao Peng, Wenjie Luo, Yiren Lu, Tianyi Shen, Cole Gulino, Ari Seff, Justin Fu
A major challenge in autonomous vehicle research is modeling agent behaviors, which has critical applications including constructing realistic and reliable simulations for off-board evaluation and forecasting traffic agents motion for onboard planning.
1 code implementation • ICCV 2023 • Ari Seff, Brian Cera, Dian Chen, Mason Ng, Aurick Zhou, Nigamaa Nayakanti, Khaled S. Refaat, Rami Al-Rfou, Benjamin Sapp
Here, we represent continuous trajectories as sequences of discrete motion tokens and cast multi-agent motion prediction as a language modeling task over this domain.
1 code implementation • ICLR 2022 • Ari Seff, Wenda Zhou, Nick Richardson, Ryan P. Adams
Parametric computer-aided design (CAD) tools are the predominant way that engineers specify physical structures, from bicycle pedals to airplanes to printed circuit boards.
1 code implementation • 16 Jul 2020 • Ari Seff, Yaniv Ovadia, Wenda Zhou, Ryan P. Adams
Parametric computer-aided design (CAD) is the dominant paradigm in mechanical engineering for physical design.
1 code implementation • NeurIPS 2019 • Ari Seff, Wenda Zhou, Farhan Damani, Abigail Doyle, Ryan P. Adams
The success of generative modeling in continuous domains has led to a surge of interest in generating discrete data such as molecules, source code, and graphs.
no code implementations • 23 May 2017 • Ari Seff, Alex Beatson, Daniel Suo, Han Liu
Developments in deep generative models have allowed for tractable learning of high-dimensional data distributions.
no code implementations • 25 Nov 2016 • Ari Seff, Jianxiong Xiao
Today's autonomous vehicles rely extensively on high-definition 3D maps to navigate the environment.
4 code implementations • 10 Jun 2015 • Fisher Yu, Ari Seff, yinda zhang, Shuran Song, Thomas Funkhouser, Jianxiong Xiao
While there has been remarkable progress in the performance of visual recognition algorithms, the state-of-the-art models tend to be exceptionally data-hungry.
no code implementations • CVPR 2015 • Hoo-chang Shin, Le Lu, Lauren Kim, Ari Seff, Jianhua Yao, Ronald M. Summers
We present an interleaved text/image deep learning system to extract and mine the semantic interactions of radiology images and reports from a national research hospital's picture archiving and communication system.
no code implementations • 12 May 2015 • Holger R. Roth, Le Lu, Jiamin Liu, Jianhua Yao, Ari Seff, Kevin Cherry, Lauren Kim, Ronald M. Summers
By leveraging existing CAD systems, coordinates of regions or volumes of interest (ROI or VOI) for lesion candidates are generated in this step and function as input for a second tier, which is our focus in this study.
no code implementations • 4 May 2015 • Hoo-chang Shin, Le Lu, Lauren Kim, Ari Seff, Jianhua Yao, Ronald M. Summers
We present an interleaved text/image deep learning system to extract and mine the semantic interactions of radiology images and reports from a national research hospital's Picture Archiving and Communication System.
no code implementations • ICCV 2015 • Chenyi Chen, Ari Seff, Alain Kornhauser, Jianxiong Xiao
To demonstrate this, we train a deep Convolutional Neural Network using recording from 12 hours of human driving in a video game and show that our model can work well to drive a car in a very diverse set of virtual environments.
1 code implementation • 15 Apr 2015 • Holger R. Roth, Christopher T. Lee, Hoo-chang Shin, Ari Seff, Lauren Kim, Jianhua Yao, Le Lu, Ronald M. Summers
We show that a data augmentation approach can help to enrich the data set and improve classification performance.
no code implementations • 14 Aug 2014 • Ari Seff, Le Lu, Kevin M. Cherry, Holger Roth, Jiamin Liu, Shijun Wang, Joanne Hoffman, Evrim B. Turkbey, Ronald M. Summers
In this paper, we propose a new algorithm representation of decomposing the LN detection problem into a set of 2D object detection subtasks on sampled CT slices, largely alleviating the curse of dimensionality issue.
no code implementations • 6 Jun 2014 • Holger R. Roth, Le Lu, Ari Seff, Kevin M. Cherry, Joanne Hoffman, Shijun Wang, Jiamin Liu, Evrim Turkbey, Ronald M. Summers
and 84%/90% at 6 FP/vol.