Search Results - "Guibas, Leonidas J."

FlowNet3D: Learning Scene Flow in 3D Point Clouds by Liu, Xingyu, Qi, Charles R., Guibas, Leonidas J.

“…Many applications in robotics and human-computer interaction can benefit from understanding 3D motion of points in a dynamic environment, widely noted as scene…”
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Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation by Wang, He, Sridhar, Srinath, Huang, Jingwei, Valentin, Julien, Song, Shuran, Guibas, Leonidas J.

“…The goal of this paper is to estimate the 6D pose and dimensions of unseen object instances in an RGB-D image. Contrary to "instance-level'' 6D pose estimation…”
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PartNet: A Large-Scale Benchmark for Fine-Grained and Hierarchical Part-Level 3D Object Understanding by Mo, Kaichun, Zhu, Shilin, Chang, Angel X., Yi, Li, Tripathi, Subarna, Guibas, Leonidas J., Su, Hao

“…We present PartNet: a consistent, large-scale dataset of 3D objects annotated with fine-grained, instance-level, and hierarchical 3D part information. Our…”
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Supervised Fitting of Geometric Primitives to 3D Point Clouds by Li, Lingxiao, Sung, Minhyuk, Dubrovina, Anastasia, Yi, Li, Guibas, Leonidas J.

“…Fitting geometric primitives to 3D point cloud data bridges a gap between low-level digitized 3D data and high-level structural information on the underlying…”
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Action-conditional implicit visual dynamics for deformable object manipulation by Shen, Bokui, Jiang, Zhenyu, Choy, Christopher, Savarese, Silvio, Guibas, Leonidas J., Anandkumar, Anima, Zhu, Yuke

“…Manipulating volumetric deformable objects in the real world, like plush toys and pizza dough, brings substantial challenges due to infinite shape variations,…”
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Gromov-Hausdorff Stable Signatures for Shapes using Persistence by Chazal, Frédéric, Cohen-Steiner, David, Guibas, Leonidas J., Mémoli, Facundo, Oudot, Steve Y.

“…We introduce a family of signatures for finite metric spaces, possibly endowed with real valued functions, based on the persistence diagrams of suitable…”
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Non-Rigid Registration Under Isometric Deformations by Huang, Qi-Xing, Adams, Bart, Wicke, Martin, Guibas, Leonidas J.

“…We present a robust and efficient algorithm for the pairwise non‐rigid registration of partially overlapping 3D surfaces. Our approach treats non‐rigid…”
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Synchronizing Probability Measures on Rotations via Optimal Transport by Birdal, Tolga, Arbel, Michael, Simsekli, Umut, Guibas, Leonidas J.

“…We introduce a new paradigm, `measure synchronization', for synchronizing graphs with measure-valued edges. We formulate this problem as maximization of the…”
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Locating and Bypassing Holes in Sensor Networks by Fang, Qing, Gao, Jie, Guibas, Leonidas J

“…In real sensor network deployments, spatial distributions of sensors are usually far from being uniform. Such networks often contain regions without enough…”
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Topological methods for exploring low-density states in biomolecular folding pathways by Yao, Yuan, Sun, Jian, Huang, Xuhui, Bowman, Gregory R, Singh, Gurjeet, Lesnick, Michael, Guibas, Leonidas J, Pande, Vijay S, Carlsson, Gunnar

“…Characterization of transient intermediate or transition states is crucial for the description of biomolecular folding pathways, which is, however, difficult…”
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HuMoR: 3D Human Motion Model for Robust Pose Estimation by Rempe, Davis, Birdal, Tolga, Hertzmann, Aaron, Yang, Jimei, Sridhar, Srinath, Guibas, Leonidas J.

“…We introduce HuMoR: a 3D Human Motion Model for Robust Estimation of temporal pose and shape. Though substantial progress has been made in estimating 3D human…”
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ImVoteNet: Boosting 3D Object Detection in Point Clouds With Image Votes by Qi, Charles R., Chen, Xinlei, Litany, Or, Guibas, Leonidas J.

“…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…”
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GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud by Yi, Li, Zhao, Wang, Wang, He, Sung, Minhyuk, Guibas, Leonidas J.

“…We introduce a novel 3D object proposal approach named Generative Shape Proposal Network (GSPN) for instance segmentation in point cloud data. Instead of…”
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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation by Charles, R. Qi, Hao Su, Mo Kaichun, Guibas, Leonidas J.

“…Point cloud is an important type of geometric data structure. Due to its irregular format, most researchers transform such data to regular 3D voxel grids or…”
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Category-Level Articulated Object Pose Estimation by Li, Xiaolong, Wang, He, Yi, Li, Guibas, Leonidas J., Abbott, A. Lynn, Song, Shuran

“…This paper addresses the task of category-level pose estimation for articulated objects from a single depth image. We present a novel category-level approach…”
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Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views by Hao Su, Qi, Charles R., Yangyan Li, Guibas, Leonidas J.

“…Object viewpoint estimation from 2D images is an essential task in computer vision. However, two issues hinder its progress: scarcity of training data with…”
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Learning Multiview 3D Point Cloud Registration by Gojcic, Zan, Zhou, Caifa, Wegner, Jan D., Guibas, Leonidas J., Birdal, Tolga

“…We present a novel, end-to-end learnable, multiview 3D point cloud registration algorithm. Registration of multiple scans typically follows a two-stage…”
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Building Markov state models with solvent dynamics by Gu, Chen, Chang, Huang-Wei, Maibaum, Lutz, Pande, Vijay S, Carlsson, Gunnar E, Guibas, Leonidas J

“…Markov state models have been widely used to study conformational changes of biological macromolecules. These models are built from short timescale simulations…”
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Volumetric and Multi-view CNNs for Object Classification on 3D Data by Qi, Charles R., Hao Su, NieBner, Matthias, Dai, Angela, Mengyuan Yan, Guibas, Leonidas J.

“…3D shape models are becoming widely available and easier to capture, making available 3D information crucial for progress in object classification. Current…”
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Robust Learning Through Cross-Task Consistency by Zamir, Amir R., Sax, Alexander, Cheerla, Nikhil, Suri, Rohan, Cao, Zhangjie, Malik, Jitendra, Guibas, Leonidas J.

“…Visual perception entails solving a wide set of tasks (e.g., object detection, depth estimation, etc). The predictions made for different tasks out of one…”
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