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Natasha Kholgade
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2020 – today
- 2024
- [c43]Manizheh Zand
, Krishna Chaitanya Kodur, Sean Banerjee
Examining Diverse Gender Dynamics in Human-Robot Interaction: Trust Privacy and Safety Perceptions. PETRA 2024 - [c42]Ava Megyeri, Noah Wiederhold, Maria Kyrarini, Sean Banerjee, Natasha Kholgade Banerjee:
GraspPC: Generating Diverse Hand Grasp Point Clouds on Objects. RO-MAN 2024: 131-138 - [c41]Ava Megyeri, Sean Banerjee, Maria Kyrarini, Natasha Kholgade Banerjee:
Using Human-Human Handover Data to Analyze Giver and Receiver Timing Relationships During the Pre-Handover Phase. RO-MAN 2024: 999-1004 - [c40]Andrew Liu, Natasha Kholgade Banerjee, Sean Banerjee:
Analyzing Perceptions on Barriers to Safety in the Workforce and Expectations on Human and Robotic Assistance. RO-MAN 2024: 1978-1983 - [i8]Mingjun Li, Numan Zafar, Natasha Kholgade Banerjee, Sean Banerjee:
Evaluating Deep Networks for Detecting User Familiarity with VR from Hand Interactions. CoRR abs/2401.16443 (2024) - [i7]Mingjun Li, Natasha Kholgade Banerjee, Sean Banerjee:
Using Motion Forecasting for Behavior-Based Virtual Reality (VR) Authentication. CoRR abs/2401.16649 (2024) - 2023
- [c39]Noah Wiederhold, Mingjun Li, Nikolas Lamb, DiMaggio Paris, Alaina Tulskie, Sean Banerjee, Natasha Kholgade Banerjee:
Studying How Object Handoff Orientations Relate to Subject Preferences on Handover. ARSO 2023: 40-45 - [c38]Gurpreet Kaur, Sean Banerjee, Natasha Kholgade Banerjee:
Perception of Human-Robot Collaboration Across Countries and Job Domains. ARSO 2023: 116-121 - [c37]Nikolas Lamb, Cameron Palmer, Benjamin Molloy, Sean Banerjee, Natasha Kholgade Banerjee:
Fantastic Breaks: A Dataset of Paired 3D Scans of Real-World Broken Objects and Their Complete Counterparts. CVPR 2023: 4681-4691 - [c36]Xinchao Song
Reinforcement-Learning Based Robotic Assembly of Fractured Objects Using Visual and Tactile Information. ICARA 2023: 170-174 - [c35]Gurpreet Kaur, Sean Banerjee, Natasha Kholgade Banerjee:
Studying Worker Perceptions on Safety, Autonomy, and Job Security in Human-Robot Collaboration. ICARA 2023: 187-191 - [c34]Richard N. C. Turner, Natasha Kholgade Banerjee, Sean Banerjee:
MoV-SLAM: Using Motion Vectors for Real-Time Single-CPU Visual SLAM. IRC 2023: 51-58 - [c33]Noah Wiederhold, Sean Banerjee, Natasha Kholgade Banerjee:
Understanding Agreement in Giver and Receiver Intentions on Grasp in Human-Human Handover. IRC 2023: 125-126 - [c32]Noah Wiederhold, Ava Megyeri, DiMaggio Paris, Sean Banerjee, Natasha Banerjee:
HOH: Markerless Multimodal Human-Object-Human Handover Dataset with Large Object Count. NeurIPS 2023 - [i6]Sichao Li, Sean Banerjee, Natasha Kholgade Banerjee, Soumyabrata Dey:
Simultaneous prediction of hand gestures, handedness, and hand keypoints using thermal images. CoRR abs/2303.01547 (2023) - [i5]Nikolas Lamb, Cameron Palmer, Benjamin Molloy, Sean Banerjee, Natasha Kholgade Banerjee:
Fantastic Breaks: A Dataset of Paired 3D Scans of Real-World Broken Objects and Their Complete Counterparts. CoRR abs/2303.14152 (2023) - [i4]Nikolas Lamb, Sean Banerjee, Natasha Kholgade Banerjee:
Pix2Repair: Implicit Shape Restoration from Images. CoRR abs/2305.18273 (2023) - [i3]Noah Wiederhold, Ava Megyeri, DiMaggio Paris, Sean Banerjee, Natasha Kholgade Banerjee:
HOH: Markerless Multimodal Human-Object-Human Handover Dataset with Large Object Count. CoRR abs/2310.00723 (2023) - 2022
- [j3]Nikolas Lamb
MendNet: Restoration of Fractured Shapes Using Learned Occupancy Functions. Comput. Graph. Forum 41(5): 65-78 (2022) - [j2]Nikolas Lamb, Sean Banerjee, Natasha Kholgade Banerjee:
DeepJoin: Learning a Joint Occupancy, Signed Distance, and Normal Field Function for Shape Repair. ACM Trans. Graph. 41(6): 230:1-230:10 (2022) - [c31]Joseph Judge, Priyo Ranjan Kundu Prosun, Owen Talmage, Austin Dykeman, Sean Banerjee, Natasha Kholgade Banerjee:
Predicting Weight and Strenuousness from High-Speed Videos of Subjects Attempting Lift. CHASE 2022: 13-24 - [c30]Austin Dykeman, Joseph Judge, Priyo Ranjan Kundu Prosun, Gurpreet Kaur, Owen Talmage, Sean Banerjee, Natasha Kholgade Banerjee:
Post-Lift Analysis of Thermal Imprint for Weight and Effort Detection. CHASE 2022: 34-45 - [c29]Nikolas Lamb
DeepMend: Learning Occupancy Functions to Represent Shape for Repair. ECCV (3) 2022: 433-450 - [c28]Richard N. C. Turner, Natasha Kholgade Banerjee, Sean Banerjee:
Using Video Motion Vectors for Structure from Motion 3D Reconstruction. SIGMAP 2022: 13-22 - [c27]Robert Miller, Natasha Kholgade Banerjee, Sean Banerjee:
Combining Real-World Constraints on User Behavior with Deep Neural Networks for Virtual Reality (VR) Biometrics. VR 2022: 409-418 - [c26]Robert Miller, Natasha Kholgade Banerjee, Sean Banerjee:
Temporal Effects in Motion Behavior for Virtual Reality (VR) Biometrics. VR 2022: 563-572 - [c25]Robert Miller, Natasha Kholgade Banerjee, Sean Banerjee:
Using External Video to Attack Behavior-Based Security Mechanisms in Virtual Reality (VR). VR Workshops 2022: 684-685 - [i2]Nikolas Lamb, Sean Banerjee, Natasha Kholgade Banerjee:
DeepMend: Learning Occupancy Functions to Represent Shape for Repair. CoRR abs/2210.05728 (2022) - [i1]Nikolas Lamb, Sean Banerjee, Natasha Kholgade Banerjee:
DeepJoin: Learning a Joint Occupancy, Signed Distance, and Normal Field Function for Shape Repair. CoRR abs/2211.12400 (2022) - 2021
- [c24]Nikolas Lamb
Using Learned Visual and Geometric Features to Retrieve Complete 3D Proxies for Broken Objects. SCF 2021: 5:1-5:15 - [c23]Robert Miller, Natasha Kholgade Banerjee, Sean Banerjee:
Using Siamese Neural Networks to Perform Cross-System Behavioral Authentication in Virtual Reality. VR 2021: 140-149 - 2020
- [c22]Jacob Gately, Ying Liang, Matthew Kolessar Wright, Natasha Kholgade Banerjee, Sean Banerjee, Soumyabrata Dey:
Automatic Material Classification Using Thermal Finger Impression. MMM (1) 2020: 239-250 - [c21]Robert Miller, Natasha Kholgade Banerjee, Sean Banerjee:
Within-System and Cross-System Behavior-Based Biometric Authentication in Virtual Reality. VR Workshops 2020: 311-316
2010 – 2019
- 2019
- [c20]Ashwin Ajit, Natasha Kholgade Banerjee, Sean Banerjee:
Combining Pairwise Feature Matches from Device Trajectories for Biometric Authentication in Virtual Reality Environments. AIVR 2019: 9-16 - [c19]Robert Miller, Ashwin Ajit, Natasha Kholgade Banerjee, Sean Banerjee:
Realtime Behavior-Based Continual Authentication of Users in Virtual Reality Environments. AIVR 2019: 253-254 - [c18]Yijun Jiang, Sean Banerjee, Natasha Kholgade Banerjee:
Predicting Human Grasp Locations on Cup Handles by Using Deep Neural Networks to Infer Heat Signatures from Depth Data. ICME Workshops 2019: 25-30 - [c17]Alexander Kupin, Benjamin Moeller, Yijun Jiang, Natasha Kholgade Banerjee, Sean Banerjee:
Task-Driven Biometric Authentication of Users in Virtual Reality (VR) Environments. MMM (1) 2019: 55-67 - [c16]Yijun Jiang, Elim Schenck, Spencer Kranz, Sean Banerjee, Natasha Kholgade Banerjee:
CNN-Based Non-contact Detection of Food Level in Bottles from RGB Images. MMM (1) 2019: 202-213 - [c15]Nikolas Lamb
Automated reconstruction of smoothly joining 3D printed restorations to fix broken objects. SCF 2019: 3:1-3:12 - 2018
- [c14]Damon Gwinn, Jordan Helmick, Natasha Kholgade Banerjee, Sean Banerjee:
Comparison of Traditional and Constrained Recursive Clustering Approaches for Generating Optimal Census Block Group Clusters. GISTAM (Selected Papers) 2018: 28-54 - [c13]Damon Gwinn, Jordan Helmick, Natasha Kholgade Banerjee, Sean Banerjee:
Optimal Estimation of Census Block Group Clusters to Improve the Computational Efficiency of Drive Time Calculations. GISTAM 2018: 96-106 - [c12]Yijun Jiang, Miao Luo, Sean Banerjee, Natasha Kholgade Banerjee:
When Will Breakfast be Ready: Temporal Prediction of Food Readiness Using Deep Convolutional Neural Networks on Thermal Videos. ICME Workshops 2018: 1-6 - [c11]Yijun Jiang, David Russell, Timothy Godisart, Natasha Kholgade Banerjee, Sean Banerjee:
Hardware Synchronization of Multiple Kinects and Microphones for 3D Audiovisual Spatiotemporal Data Capture. ICME 2018: 1-6 - [c10]Hunter Quant, Sean Banerjee, Natasha Kholgade Banerjee:
A Virtual Reality Interface for Interactions with Spatiotemporal 3D Data. MMM (2) 2018: 343-347 - [c9]Lintao Guo, Hunter Quant, Nikolas Lamb
Multi-camera Microenvironment to Capture Multi-view Time-Lapse Videos for 3D Analysis of Aging Objects. MMM (2) 2018: 381-385 - [c8]Nikolas Lamb
Programmatic 3D Printing of a Revolving Camera Track to Automatically Capture Dense Images for 3D Scanning of Objects. MMM (2) 2018: 390-394 - [c7]Lintao Guo, Hunter Quant, Nikolas Lamb
Spatiotemporal 3D Models of Aging Fruit from Multi-view Time-Lapse Videos. MMM (1) 2018: 466-478 - [c6]Tim Dunn, Sean Banerjee, Natasha Kholgade Banerjee:
User-Independent Detection of Swipe Pressure Using a Thermal Camera for Natural Surface Interaction. MMSP 2018: 1-6 - 2016
- [c5]Yan Gao, Daqing Hou, Natasha Banerjee, Sean Banerjee:
Water Fixture Identification in Smart Housing: A Domain Knowledge Based Case Study. ICMLA 2016: 904-909 - [c4]Zhe Cao, Yaser Sheikh, Natasha Kholgade Banerjee:
Real-time scalable 6DOF pose estimation for textureless objects. ICRA 2016: 2441-2448 - [c3]Tim Dunn, Natasha Kholgade Banerjee, Sean Banerjee:
GPU Acceleration of Document Similarity Measures for Automated Bug Triaging. ISSRE Workshops 2016: 140-145 - 2015
- [b1]Natasha Kholgade:
3D Manipulation of Objects in Photographs. Carnegie Mellon University, USA, 2015 - 2014
- [j1]Natasha Kholgade, Tomas Simon, Alexei A. Efros
3D object manipulation in a single photograph using stock 3D models. ACM Trans. Graph. 33(4): 127:1-127:12 (2014) - 2011
- [c2]Natasha Kholgade, Iain A. Matthews, Yaser Sheikh:
Content Retargeting Using Parameter-Parallel Facial Layers. Symposium on Computer Animation 2011: 195-204
2000 – 2009
- 2009
- [c1]Natasha Kholgade, Andreas E. Savakis:
Human Activity Recognition Using the 4D Spatiotemporal Shape Context Descriptor. ISVC (2) 2009: 357-366
Coauthor Index
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last updated on 2024-11-11 22:27 CET by the dblp team
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