173 citations · 215 across the 11 of their papers we have counts for
16 papers
Orion: A Unified Visual Agent for Multimodal Perception, Advanced Visual Reasoning and Execution
N Dinesh Reddy, Dylan Snyder, Lona Kiragu +3
We introduce Orion, a visual agent that integrates vision-based reasoning with tool-augmented execution to achieve powerful, precise, multi-step visual intelligence across images,…
Finding Label and Model Errors in Perception Data With Learned Observation Assertions
Daniel Kang, Nikos Arechiga, Sudeep Pillai +2
ML is being deployed in complex, real-world scenarios where errors have impactful consequences. In these systems, thorough testing of the ML pipelines is critical. A key component…
PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving
Kuan-Hui Lee, Matthew Kliemann, Adrien Gaidon +4
In autonomous driving, accurately estimating the state of surrounding obstacles is critical for safe and robust path planning. However, this perception task is difficult, particula…
Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion
Igor Vasiljevic, Vitor Guizilini, Rares Ambrus +4
Self-supervised learning has emerged as a powerful tool for depth and ego-motion estimation, leading to state-of-the-art results on benchmark datasets. However, one significant lim…
Neural Outlier Rejection for Self-Supervised Keypoint Learning
Jiexiong Tang, Hanme Kim, Vitor Guizilini +2
Identifying salient points in images is a crucial component for visual odometry, Structure-from-Motion or SLAM algorithms. Recently, several learned keypoint methods have demonstra…
Self-Supervised 3D Keypoint Learning for Ego-motion Estimation
Jiexiong Tang, Rares Ambrus, Vitor Guizilini +4
Detecting and matching robust viewpoint-invariant keypoints is critical for visual SLAM and Structure-from-Motion. State-of-the-art learning-based methods generate training samples…
Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances
Vitor Guizilini, Jie Li, Rares Ambrus +2
Dense depth estimation from a single image is a key problem in computer vision, with exciting applications in a multitude of robotic tasks. Initially viewed as a direct regression…
Two Stream Networks for Self-Supervised Ego-Motion Estimation
Rares Ambrus, Vitor Guizilini, Jie Li +2
Learning depth and camera ego-motion from raw unlabeled RGB video streams is seeing exciting progress through self-supervision from strong geometric cues. To leverage not only appe…
Self-Supervised Visual Place Recognition Learning in Mobile Robots
Sudeep Pillai, John Leonard
Place recognition is a critical component in robot navigation that enables it to re-establish previously visited locations, and simultaneously use this information to correct the d…
3D Packing for Self-Supervised Monocular Depth Estimation
Vitor Guizilini, Rares Ambrus, Sudeep Pillai +2
Although cameras are ubiquitous, robotic platforms typically rely on active sensors like LiDAR for direct 3D perception. In this work, we propose a novel self-supervised monocular…
SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation
Sudeep Pillai, Rares Ambrus, Adrien Gaidon
Recent techniques in self-supervised monocular depth estimation are approaching the performance of supervised methods, but operate in low resolution only. We show that high resolut…
Towards Visual Ego-motion Learning in Robots
Sudeep Pillai, John J. Leonard
Many model-based Visual Odometry (VO) algorithms have been proposed in the past decade, often restricted to the type of camera optics, or the underlying motion manifold observed. W…
High-Performance and Tunable Stereo Reconstruction
Sudeep Pillai, Srikumar Ramalingam, John J. Leonard
Traditional stereo algorithms have focused their efforts on reconstruction quality and have largely avoided prioritizing for run time performance. Robots, on the other hand, requir…
Monocular SLAM Supported Object Recognition
Sudeep Pillai, John Leonard
In this work, we develop a monocular SLAM-aware object recognition system that is able to achieve considerably stronger recognition performance, as compared to classical object rec…
Learning Articulated Motions From Visual Demonstration
Sudeep Pillai, Matthew R. Walter, Seth Teller
Many functional elements of human homes and workplaces consist of rigid components which are connected through one or more sliding or rotating linkages. Examples include doors and…
Bitcoin Transaction Graph Analysis
Michael Fleder, Michael S. Kester, Sudeep Pillai
Bitcoins have recently become an increasingly popular cryptocurrency through which users trade electronically and more anonymously than via traditional electronic transfers. Bitcoi…