Computer vision
Related papers: 20
About
Computer vision is the field of artificial intelligence concerned with enabling machines to interpret and understand visual information from the world — including images, video, depth maps, and point clouds. In robotics and AI, it serves as a foundational sensing capability, allowing systems to perceive their surroundings, recognize objects, estimate poses, navigate environments, and interact with physical elements. Key applications include autonomous driving, where cameras and LiDAR streams are processed to detect obstacles and lanes; visual SLAM, where robots simultaneously build maps and localize themselves using camera feeds; visual servoing, where real-time image data guides robotic manipulators; and 6D object pose estimation, which enables precise grasping. Modern computer vision increasingly relies on deep learning techniques, such as convolutional neural networks, to extract meaningful features from raw sensor data. Benchmarks like KITTI have been instrumental in advancing the field by providing standardized evaluation datasets. Computer vision matters because it bridges the gap between raw sensor input and actionable robot behavior, making autonomous and intelligent systems practical in unstructured, real-world environments.
Top Researchers
Top Cited Papers
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
Citations: 14348 • 2012
Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, Raquel Urtasun
Citations: 9681 • 2013
A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses
R. Tsai
Citations: 5813 • 1987
Color indexing
Michael J. Swain, Dana H. Ballard
Citations: 5591 • 1991
Robot Motion Planning
Jean‐Claude Latombe
Citations: 5429 • 1991
3D is here: Point Cloud Library (PCL)
Radu Bogdan Rusu, Steve Cousins
Citations: 4825 • 2011
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Yin Zhou, Oncel Tuzel
Citations: 4542 • 2018
VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
Tong Qin, Peiliang Li, Shaojie Shen
Citations: 4390 • 2018
Parallel Tracking and Mapping for Small AR Workspaces
Georg Klein, David W. Murray
Citations: 4244 • 2007
Simultaneous localization and mapping: part I
Hugh Durrant‐Whyte, T. Bailey
Citations: 4107 • 2006
Computer and Robot Vision
Robert M. Haralock, Linda G. Shapiro
Citations: 3952 • 1991
A benchmark for the evaluation of RGB-D SLAM systems
Jrgen Sturm, Nikolas Engelhard, Felix Endres, Wolfram Burgard, Daniel Cremers
Citations: 3918 • 2012
MonoSLAM: Real-Time Single Camera SLAM
Andrew J. Davison, Ian Reid, Nicholas Molton, Olivier Stasse
Citations: 3909 • 2007
Robot Vision
Berthold K. P. Horn
Citations: 3635 • 1986
VoxNet: A 3D Convolutional Neural Network for real-time object recognition
Daniel Maturana, Sebastian Scherer
Citations: 3579 • 2015
A tutorial on visual servo control
Seth Hutchinson, Gregory D. Hager, Peter Corke
Citations: 3499 • 1996
SECOND: Sparsely Embedded Convolutional Detection
Yan Yan, Yuxing Mao, Bo Li
Citations: 3212 • 2018
Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age
César Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, José Neira, Ian Reid, John J. Leonard
Citations: 3158 • 2016
Domain randomization for transferring deep neural networks from simulation to the real world
Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, Pieter Abbeel
Citations: 2736 • 2017
Manipulability of Robotic Mechanisms
Tsuneo Yoshikawa
Citations: 2516 • 1985