1 code implementation • 10 Nov 2023 • Xiaoyi Cai, Siddharth Ancha, Lakshay Sharma, Philip R. Osteen, Bernadette Bucher, Stephen Phillips, Jiuguang Wang, Michael Everett, Nicholas Roy, Jonathan P. How
For uncertainty quantification, we efficiently model both aleatoric and epistemic uncertainty by learning discrete traction distributions and probability densities of the traction predictor's latent features.
no code implementations • 24 Feb 2023 • Siddharth Ancha, Gaurav Pathak, Ji Zhang, Srinivasa Narasimhan, David Held
To navigate in an environment safely and autonomously, robots must accurately estimate where obstacles are and how they move.
no code implementations • 1 Feb 2022 • Jianren Wang, Haiming Gang, Siddharth Ancha, Yi-Ting Chen, David Held
However, these detectors usually require training on large amounts of annotated data that is expensive and time-consuming to collect.
no code implementations • 8 Jul 2021 • Siddharth Ancha, Gaurav Pathak, Srinivasa G. Narasimhan, David Held
We use light curtains to estimate the safety envelope of a scene: a hypothetical surface that separates the robot from all obstacles.
no code implementations • CVPR 2021 • Yaadhav Raaj, Siddharth Ancha, Robert Tamburo, David Held, Srinivasa G. Narasimhan
Active sensing through the use of Adaptive Depth Sensors is a nascent field, with potential in areas such as Advanced driver-assistance systems (ADAS).
no code implementations • 9 Oct 2020 • Jianing Qian, Junyu Nan, Siddharth Ancha, Brian Okorn, David Held
Current state-of-the-art trackers often fail due to distractorsand large object appearance changes.
1 code implementation • 18 Aug 2020 • Jianren Wang, Siddharth Ancha, Yi-Ting Chen, David Held
Instead, we propose leveraging vast unlabeled datasets by self-supervised metric learning of 3D object trackers, with a focus on data association.
no code implementations • ECCV 2020 • Siddharth Ancha, Yaadhav Raaj, Peiyun Hu, Srinivasa G. Narasimhan, David Held
Most real-world 3D sensors such as LiDARs perform fixed scans of the entire environment, while being decoupled from the recognition system that processes the sensor data.
2 code implementations • 27 Dec 2019 • Siddharth Ancha, Junyu Nan, David Held
For a reliable detection system, if a high confidence detection is made, we would want high certainty that the object has indeed been detected.
3 code implementations • 22 May 2018 • Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison Cottrell, Antonio Criminisi, Aditya Nori
We propose the autofocus convolutional layer for semantic segmentation with the objective of enhancing the capabilities of neural networks for multi-scale processing.
Ranked #5 on Brain Tumor Segmentation on BRATS-2015
no code implementations • NeurIPS 2016 • Roger B. Grosse, Siddharth Ancha, Daniel M. Roy
Markov chain Monte Carlo (MCMC) is one of the main workhorses of probabilistic inference, but it is notoriously hard to measure the quality of approximate posterior samples.