2.3k citations · 4.5k across the 63 of their papers we have counts for
11 papers · 1 filter
Learning Predictive Models From Observation and Interaction
Karl Schmeckpeper, Annie Xie, Oleh Rybkin +4
Learning predictive models from interaction with the world allows an agent, such as a robot, to learn about how the world works, and then use this learned model to plan coordinated…
EventGAN: Leveraging Large Scale Image Datasets for Event Cameras
Alex Zihao Zhu, Ziyun Wang, Kaung Khant +1
Event cameras provide a number of benefits over traditional cameras, such as the ability to track incredibly fast motions, high dynamic range, and low power consumption. However, t…
TexturePose: Supervising Human Mesh Estimation with Texture Consistency
Georgios Pavlakos, Nikos Kolotouros, Kostas Daniilidis
This work addresses the problem of model-based human pose estimation. Recent approaches have made significant progress towards regressing the parameters of parametric human body mo…
TagSLAM: Robust SLAM with Fiducial Markers
Bernd Pfrommer, Kostas Daniilidis
TagSLAM provides a convenient, flexible, and robust way of performing Simultaneous Localization and Mapping (SLAM) with AprilTag fiducial markers. By leveraging a few simple abstra…
Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop
Nikos Kolotouros, Georgios Pavlakos, Michael J. Black +1
Model-based human pose estimation is currently approached through two different paradigms. Optimization-based methods fit a parametric body model to 2D observations in an iterative…
Convolutional Mesh Regression for Single-Image Human Shape Reconstruction
Nikos Kolotouros, Georgios Pavlakos, Kostas Daniilidis
This paper addresses the problem of 3D human pose and shape estimation from a single image. Previous approaches consider a parametric model of the human body, SMPL, and attempt to…
Event-based Vision: A Survey
Guillermo Gallego, Tobi Delbruck, Garrick Orchard +8
Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness ch…
Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning
Karl Pertsch, Oleh Rybkin, Jingyun Yang +5
Temporal observations such as videos contain essential information about the dynamics of the underlying scene, but they are often interleaved with inessential, predictable details.…
Equivariant Multi-View Networks
Carlos Esteves, Yinshuang Xu, Christine Allen-Blanchette +1
Several popular approaches to 3D vision tasks process multiple views of the input independently with deep neural networks pre-trained on natural images, achieving view permutation…
Motion Equivariant Networks for Event Cameras with the Temporal Normalization Transform
Alex Zihao Zhu, Ziyun Wang, Kostas Daniilidis
In this work, we propose a novel transformation for events from an event camera that is equivariant to optical flow under convolutions in the 3-D spatiotemporal domain. Events are…
All Graphs Lead to Rome: Learning Geometric and Cycle-Consistent Representations with Graph Convolutional Networks
Stephen Phillips, Kostas Daniilidis
Image feature matching is a fundamental part of many geometric computer vision applications, and using multiple images can improve performance. In this work, we formulate multi-ima…