190 citations · 998 across the 71 of their papers we have counts for
11 papers · 1 filter
Human 3D keypoints via spatial uncertainty modeling
Francis Williams, Or Litany, Avneesh Sud +2
We introduce a technique for 3D human keypoint estimation that directly models the notion of spatial uncertainty of a keypoint. Our technique employs a principled approach to model…
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection
He Wang, Yezhen Cong, Or Litany +2
3D object detection is an important yet demanding task that heavily relies on difficult to obtain 3D annotations. To reduce the required amount of supervision, we propose 3DIoUMatc…
Learned Equivariant Rendering without Transformation Supervision
Cinjon Resnick, Or Litany, Hugo Larochelle +2
We propose a self-supervised framework to learn scene representations from video that are automatically delineated into objects and background. Our method relies on moving objects…
ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation
Fei Xia, Chengshu Li, Roberto Martín-Martín +3
Many Reinforcement Learning (RL) approaches use joint control signals (positions, velocities, torques) as action space for continuous control tasks. We propose to lift the action s…
Object-Centric Multi-View Aggregation
Shubham Tulsiani, Or Litany, Charles R. Qi +2
We present an approach for aggregating a sparse set of views of an object in order to compute a semi-implicit 3D representation in the form of a volumetric feature grid. Key to our…
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
Saining Xie, Jiatao Gu, Demi Guo +3
Arguably one of the top success stories of deep learning is transfer learning. The finding that pre-training a network on a rich source set (eg., ImageNet) can help boost performan…
Representation Learning Through Latent Canonicalizations
Or Litany, Ari Morcos, Srinath Sridhar +2
We seek to learn a representation on a large annotated data source that generalizes to a target domain using limited new supervision. Many prior approaches to this problem have foc…
Continuous Geodesic Convolutions for Learning on 3D Shapes
Zhangsihao Yang, Or Litany, Tolga Birdal +2
The majority of descriptor-based methods for geometric processing of non-rigid shape rely on hand-crafted descriptors. Recently, learning-based techniques have been shown effective…
On Learning Sets of Symmetric Elements
Haggai Maron, Or Litany, Gal Chechik +1
Learning from unordered sets is a fundamental learning setup, recently attracting increasing attention. Research in this area has focused on the case where elements of the set are…
ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes
Charles R. Qi, Xinlei Chen, Or Litany +1
3D object detection has seen quick progress thanks to advances in deep learning on point clouds. A few recent works have even shown state-of-the-art performance with just point clo…
The Whole Is Greater Than the Sum of Its Nonrigid Parts
Oshri Halimi, Ido Imanuel, Or Litany +4
According to Aristotle, a philosopher in Ancient Greece, "the whole is greater than the sum of its parts". This observation was adopted to explain human perception by the Gestalt p…