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Elsevier DOI
1211
Visual system; Grasping movements; Motion analysis; Hand posture; Hand
gesture; Object recognition
BibRef
Sreenivasa, M.,
Soueres, P.,
Laumond, J.P.,
Walking to Grasp: Modeling of Human Movements as Invariants and an
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SMC-A(42), No. 4, July 2012, pp. 880-893.
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1206
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Rosell, J.,
Hybrid Mapping for the Assistance of Teleoperated Grasping Tasks,
SMCS(43), No. 2, March 2013, pp. 390-401.
IEEE DOI
1303
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Richtsfeld, A.[Andreas],
Varadarajan, K.M.[Karthik Mahesh],
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Vincze, M.[Markus],
Combining Plane Estimation with Shape Detection for Holistic Scene
Understanding,
ACIVS11(736-747).
Springer DOI
1108
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Varadarajan, K.M.[Karthik Mahesh],
Vincze, M.[Markus],
AfNet: The Affordance Network,
ACCV12(I:512-523).
Springer DOI
1304
BibRef
Earlier:
Knowledge Representation and Inference for Grasp Affordances,
CVS11(173-182).
Springer DOI
1109
BibRef
And:
Surface reconstruction for RGB-D data using real-time depth propagation,
Dense11(723-724).
IEEE DOI
1201
BibRef
Earlier:
Real-time depth diffusion for 3D surface reconstruction,
ICIP10(4149-4152).
IEEE DOI
1009
BibRef
Olufs, S.[Sven],
Vincze, M.[Markus],
Room-structure estimation in Manhattan-like environments from dense 2˝D
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WACV11(118-124).
IEEE DOI
1101
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Richtsfeld, M.[Mario],
Vincze, M.[Markus],
Point Cloud Segmentation Based on Radial Reflection,
CAIP09(955-962).
Springer DOI
0909
BibRef
Lee, C.S.[Chan-Su],
Chun, S.[Sung_Yong],
Park, S.W.[Shin Won],
Tracking hand rotation and various grasping gestures from an IR
camera using extended cylindrical manifold embedding,
CVIU(117), No. 12, 2013, pp. 1711-1723.
Elsevier DOI
1310
BibRef
Earlier: A1, A3, Only:
Tracking Hand Rotation and Grasping from an IR Camera Using Cylindrical
Manifold Embedding,
ICPR10(2612-2615).
IEEE DOI
1008
Tracking
BibRef
Song, K.T.,
Jiang, S.Y.,
Lin, M.H.,
Interactive Teleoperation of a Mobile Manipulator Using a
Shared-Control Approach,
HMS(46), No. 6, December 2016, pp. 834-845.
IEEE DOI
1612
Grasping
BibRef
Cotugno, G.,
Althoefer, K.,
Nanayakkara, T.,
The Role of the Thumb: Study of Finger Motion in Grasping and
Reachability Space in Human and Robotic Hands,
SMCS(47), No. 7, July 2017, pp. 1061-1070.
IEEE DOI
1706
Grasping, Grippers, Kinematics, Robot kinematics, Standards, Thumb,
Dexterous manipulation, grasping, humanoid robots, kinematics,
multifingered, hands
BibRef
Cai, M.,
Kitani, K.M.,
Sato, Y.,
An Ego-Vision System for Hand Grasp Analysis,
HMS(47), No. 4, August 2017, pp. 524-535.
IEEE DOI
1708
Cameras, Feature extraction, Image segmentation, Robots, Sensors,
Taxonomy, Visualization, Egocentric vision, hand grasp, recognition,
wearable, system
BibRef
Song, P.[Peng],
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Grasp planning via hand-object geometric fitting,
VC(34), No. 2, February 2018, pp. 257-270.
WWW Link.
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A Multi-Modal, Discriminative and Spatially Invariant CNN for RGB-D
Object Labeling,
PAMI(40), No. 9, September 2018, pp. 2051-2065.
IEEE DOI
1808
BibRef
Earlier:
Model-Free Segmentation and Grasp Selection of Unknown Stacked Objects,
ECCV14(V: 659-674).
Springer DOI
1408
Labeling, Solid modeling, Proposals,
Semantics, Image reconstruction, Computational modeling,
semantic segmentation
BibRef
González-Díaz, I.[Iván],
Benois-Pineau, J.[Jenny],
Domenger, J.P.[Jean-Philippe],
Cattaert, D.[Daniel],
de Rugy, A.[Aymar],
Perceptually-guided deep neural networks for ego-action prediction:
Object grasping,
PR(88), 2019, pp. 223-235.
Elsevier DOI
1901
Human perception, Grasping action prediction,
Weakly supervised active object detection
BibRef
Chauhan, R.,
Sebastian, B.,
Ben-Tzvi, P.,
Grasp Prediction Toward Naturalistic Exoskeleton Glove Control,
HMS(50), No. 1, February 2020, pp. 22-31.
IEEE DOI
2001
Prediction algorithms, Exoskeletons,
Principal component analysis, Sensors, Electromyography,
upper limb
BibRef
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Sahillioglu, Y.[Yusuf],
3D indirect shape retrieval based on hand interaction,
VC(36), No. 1, January 2020, pp. 5-17.
WWW Link.
2001
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Zhang, H.,
Zhou, X.,
Lan, X.,
Li, J.,
Tian, Z.,
Zheng, N.,
A Real-Time Robotic Grasping Approach With Oriented Anchor Box,
SMCS(51), No. 5, May 2021, pp. 3014-3025.
IEEE DOI
2104
Robot kinematics, Grasping, Feature extraction, Training,
Real-time systems, Prediction algorithms, Angle matching,
real-time robotic grasping
BibRef
de Gregorio, D.[Daniele],
Zanella, R.[Riccardo],
Palli, G.[Gianluca],
di Stefano, L.[Luigi],
Effective Deployment of CNNs for 3DoF Pose Estimation and Grasping in
Industrial Settings,
ICPR21(7419-7426)
IEEE DOI
2105
Deep learning, Training, Automation, Service robots, Pose estimation,
Training data, Grasping
BibRef
Arora, P.[Prateek],
Papachristos, C.[Christos],
Mobile Manipulator Robot Visual Servoing and Guidance for Dynamic
Target Grasping,
ISVC20(II:223-235).
Springer DOI
2103
BibRef
Karunratanakul, K.,
Tang, S.[Siyu],
Zhang, Y.,
Black, M.J.,
Muandet, K.[Krikamol],
Tang, S.,
Grasping Field: Learning Implicit Representations for Human Grasps,
3DV20(333-344)
IEEE DOI
2102
Grasping, Solid modeling,
Image reconstruction, Neural networks, Task analysis, Data models,
grasp generation
BibRef
Taheri, O.[Omid],
Ghorbani, N.[Nima],
Black, M.J.[Michael J.],
Tzionas, D.[Dimitrios],
Grab: A Dataset of Whole-body Human Grasping of Objects,
ECCV20(IV:581-600).
Springer DOI
2011
BibRef
Gong, S.,
Bahri, M.,
Bronstein, M.M.,
Zafeiriou, S.P.[Stefanos P.],
Geometrically Principled Connections in Graph Neural Networks,
CVPR20(11412-11421)
IEEE DOI
2008
Convolution, Neural networks, Machine learning, Kernel,
Interpolation, Task analysis, Shape
BibRef
Fang, H.,
Wang, C.,
Gou, M.,
Lu, C.,
GraspNet-1Billion: A Large-Scale Benchmark for General Object
Grasping,
CVPR20(11441-11450)
IEEE DOI
2008
Grasping, Cameras,
Robot vision systems, Benchmark testing, Machine learning, Robustness
BibRef
Shan, D.,
Geng, J.,
Shu, M.,
Fouhey, D.F.,
Understanding Human Hands in Contact at Internet Scale,
CVPR20(9866-9875)
IEEE DOI
2008
Videos, Internet, Image reconstruction, YouTube,
Computer vision, Data mining
BibRef
James, S.[Stephen],
Wohlhart, P.[Paul],
Kalakrishnan, M.[Mrinal],
Kalashnikov, D.[Dmitry],
Irpan, A.[Alex],
Ibarz, J.[Julian],
Levine, S.[Sergey],
Hadsell, R.[Raia],
Bousmalis, K.[Konstantinos],
Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via
Randomized-To-Canonical Adaptation Networks,
CVPR19(12619-12629).
IEEE DOI
2002
BibRef
Brahmbhatt, S.[Samarth],
Ham, C.[Cusuh],
Kemp, C.C.[Charles C.],
Hays, J.[James],
ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging,
CVPR19(8701-8711).
IEEE DOI
2002
BibRef
Tang, Q.[Qirong],
Hu, X.[Xue],
Chu, Z.[Zhugang],
Wu, S.[Shun],
6d Gripper Pose Estimation from RGB-D Image,
CVS19(120-125).
Springer DOI
1912
BibRef
Kiatos, M.[Marios],
Malassiotis, S.[Sotiris],
Grasping Unknown Objects by Exploiting Complementarity with Robot Hand
Geometry,
CVS19(88-97).
Springer DOI
1912
BibRef
Gritsenko, P.[Pavel],
Gritsenko, I.[Igor],
Seidakhmet, A.[Askar],
Kwolek, B.[Bogdan],
Plane-Based Humanoid Robot Navigation and Object Model Construction for
Grasping,
4DPose18(I:649-664).
Springer DOI
1905
BibRef
Ghazaei, G.[Ghazal],
Laina, I.[Iro],
Rupprecht, C.[Christian],
Tombari, F.[Federico],
Navab, N.[Nassir],
Nazarpour, K.[Kianoush],
Dealing with Ambiguity in Robotic Grasping via Multiple Predictions,
ACCV18(IV:38-55).
Springer DOI
1906
BibRef
Gupta, K.,
Burschka, D.,
Bhavsar, A.,
Effectiveness of Grasp Attributes and Motion-Constraints for
Fine-Grained Recognition of Object Manipulation Actions,
Hands16(1232-1239)
IEEE DOI
1612
BibRef
de Gregorio, D.[Daniele],
Tombari, F.[Federico],
di Stefano, L.[Luigi],
RobotFusion: Grasping with a Robotic Manipulator via Multi-view
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6DPose16(III: 634-647).
Springer DOI
1611
BibRef
Lakani, S.R.[Safoura Rezapour],
Rodríguez-Sánchez, A.J.[Antonio J.],
Piater, J.H.[Justus H.],
Can Affordances Guide Object Decomposition into Semantically
Meaningful Parts?,
WACV17(82-90)
IEEE DOI
1609
Computer vision, Grasping, Histograms, Semantics, Shape, Visualization
BibRef
Yang, Y.Z.[Ye-Zhou],
Fermuller, C.[Cornelia],
Li, Y.[Yi],
Aloimonos, Y.[Yiannis],
Grasp type revisited:
A modern perspective on a classical feature for vision,
CVPR15(400-408)
IEEE DOI
1510
BibRef
Huang, D.A.[De-An],
Ma, M.H.[Ming-Huang],
Ma, W.C.[Wei-Chiu],
Kitani, K.M.[Kris M.],
How do we use our hands? Discovering a diverse set of common grasps,
CVPR15(666-675)
IEEE DOI
1510
BibRef
Lakani, S.R.[Safoura Rezapour],
Popa, M.[Mirela],
Rodriguez-Sanchez, A.J.[Antonio J.],
Piater, J.H.[Justus H.],
CPS: 3D Compositional Part Segmentation through Grasping,
CRV15(117-124)
IEEE DOI
1507
Feature extraction
BibRef
Kim, J.W.,
You, S.,
Ji, S.H.,
Kim, H.S.,
Real-Time Hand Grasp Recognition Using Weakly Supervised Two-Stage
Convolutional Neural Networks for Understanding Manipulation Actions,
DeepLearnRV17(481-483)
IEEE DOI
1709
Feature extraction, Grasping, Image recognition,
Network architecture, Pattern recognition, Real-time, systems
BibRef
Thonnagith, P.,
Sudsang, A.,
New hand posture classification strategy for finding
kinematically-feasible precision grasps,
ICARCV10(1583-1588).
IEEE DOI
1109
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Wörsdörfer, F.[Florian],
Stock, F.[Florian],
Bayro-Corrochano, E.[Eduardo],
Hildenbrand, D.[Dietmar],
Optimizations and Performance of a Robotics Grasping Algorithm
Described in Geometric Algebra,
CIARP09(263-271).
Springer DOI
0911
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Yasumuro, Y.[Yoshihiro],
Yamazaki, M.[Masayuki],
Imura, M.[Masataka],
Manabe, Y.[Yoshitsugu],
Chihara, K.[Kunihiro],
Grasp Motion Synthesis Based on Object Features,
AMDO06(305-314).
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0607
BibRef
Taylor, M.J.,
Blake, A.,
Grasping the Apparent Contour,
ECCV94(B:25-34).
Springer DOI
BibRef
9400
Blake, A.,
Taylor, M.J., and
Cox, A.,
Grasping Visual Symmetry,
ICCV93(724-733).
IEEE DOI Symmetry as the locus of bi-tangent circles.
BibRef
9300
Gatrell, L.B.[Lance B.],
CAD-Based Grasp Synthesis Utilizing Polygons, Edges, and Vertices,
CRA89(184-189).
BibRef
8900
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Carried Objects, Carrying Objects .