926 citations · 2.2k across the 54 of their papers we have counts for
8 papers · 1 filter
Learning to Manipulate Tools by Aligning Simulation to Video Demonstration
Kateryna Zorina, Justin Carpentier, Josef Sivic +1
A seamless integration of robots into human environments requires robots to learn how to use existing human tools. Current approaches for learning tool manipulation skills mostly r…
Estimating 3D Motion and Forces of Human-Object Interactions from Internet Videos
Zongmian Li, Jiri Sedlar, Justin Carpentier +3
In this paper, we introduce a method to automatically reconstruct the 3D motion of a person interacting with an object from a single RGB video. Our method estimates the 3D poses of…
Weakly Supervised Human-Object Interaction Detection in Video via Contrastive Spatiotemporal Regions
Shuang Li, Yilun Du, Antonio Torralba +2
We introduce the task of weakly supervised learning for detecting human and object interactions in videos. Our task poses unique challenges as a system does not know what types of…
Reconstructing and grounding narrated instructional videos in 3D
Dimitri Zhukov, Ignacio Rocco, Ivan Laptev +4
Narrated instructional videos often show and describe manipulations of similar objects, e.g., repairing a particular model of a car or laptop. In this work we aim to reconstruct su…
Learning to solve geometric construction problems from images
J. Macke, J. Sedlar, M. Olsak +2
We describe a purely image-based method for finding geometric constructions with a ruler and compass in the Euclidea geometric game. The method is based on adapting the Mask R-CNN…
Single-view robot pose and joint angle estimation via render & compare
Yann Labbé, Justin Carpentier, Mathieu Aubry +1
We introduce RoboPose, a method to estimate the joint angles and the 6D camera-to-robot pose of a known articulated robot from a single RGB image. This is an important problem to g…
Visualizing computation in large-scale cellular automata
Hugo Cisneros, Josef Sivic, Tomas Mikolov
Emergent processes in complex systems such as cellular automata can perform computations of increasing complexity, and could possibly lead to artificial evolution. Such a feat woul…
Thinking Fast and Slow: Efficient Text-to-Visual Retrieval with Transformers
Antoine Miech, Jean-Baptiste Alayrac, Ivan Laptev +2
Our objective is language-based search of large-scale image and video datasets. For this task, the approach that consists of independently mapping text and vision to a joint embedd…