Thesis
Continuous-state Graphical Models for Object Localization, Pose Estimation and Tracking, L. Sigal, PhD Thesis, May 2008. |
Books
Visual Analysis of Humans: Looking at People, T. Moeslund, A. Hilton, V. Krüger and L. Sigal (Eds). ISBN: ISBN 978-0-85729-996-3. To be published by Springer Verlag in October 2011. |
Book Chapters
Human Pose Estimation,
L. Sigal,
Encyclopedia of Computer Vision, Springer, 2011. (accepted) | |
Benchmark Datasets for Pose Estimation and Tracking,
M. Andriluka, L. Sigal and M. J. Black,
Visual Analysis of Humans: Looking at People,
T. Moeslund, A. Hilton, V. Krüger and L. Sigal (Eds). ISBN: ISBN 978-0-85729-996-3. To be published by Springer Verlag in October 2011. | |
Video-Based People Tracking,
M. Brubaker, L. Sigal and D. Fleet,
Handbook on Ambient Intelligence and Smart Environments, H. Nakashima, H. Aghajan, and J.C. Augusto (Eds), Springer Verlag, 2009. | |
Dynamics and Control of Multibody Systems,
M. Vondrak, L. Sigal and O. C. Jenkins,
Motion Control, A. Lazinica (Eds), ISBN978-953-7619-X-X, 2009. To be published by
IN-TECH, Vienna in September 2009. (accepted) |
Journal Articles
TMLR'24 | |
TPAMI'24 | |
Pattern Recognition'24 | |
TPAMI'23 | |
TMLR'23 | |
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment,
J. Wang, J. Chen, J. Lin, L. Sigal and C. W. de Silva,
Pattern Recognition (PR), 2021. | |
DeepVS2.0: A Saliency-Structured Deep Learning Method for Predicting Dynamic Visual Attention,
L. Jiang, M. Xu, Z. Wang and L. Sigal,
International Journal of Computer Vision (IJCV), 2021. | |
PolyFit: Perception- Aligned Vectorization of Raster Clip-Art via Intermediate Polygonal Fitting,
E. A. Dominici, N. Schertler, J. Griffin, S. Hoshyari, L. Sigal and A. Sheffer,
ACM Transactions on Graphics (ACM SIGGRAPH), 2020. | |
DeepCT: A novel deep complex-valued network with learnable transform for video saliency prediction,
L. Jiang, M. Xu, S. Zhang and L. Sigal,
Pattern Recognition (PR), 2020. | |
Layout2image: Image Generation from Layout,
B. Zhao, W. Yin, L. Meng and L. Sigal,
International Journal of Computer Vision (IJCV), 2020. | |
Recent advances in zero-shot recognition: Toward data-efficient understanding of visual content,
Y. Fu, T. Xiang, Y.G. Jiang, X. Xue, L. Sigal and S. Gong,
IEEE Signal Processing Magazine, 2019. | |
Multi-level semantic feature augmentation for one-shot learning,
Z. Chen, Y. Fu, Y. Zhang, Y.G. Jiang, X. Xue and L. Sigal,
IEEE Transactions on Image Processing (TIP), 2019. | |
Learning to generate posters of scientific papers by probabilistic graphical models,
Y.T. Qiang, Y.W. Fu, X. Yu, Y.W. Guo, Z.H. Zhou and L. Sigal,
Journal of Computer Science and Technology, 2019. | |
Predicting Personality from Book Preferences with User-Generated Content Labels,
N. Annalyn, M. W. Bos, L. Sigal and B. Li,
IEEE Transactions on Affective Computing (TAC), 2018. | |
Story Albums: Creating Fictional Stories from Personal Photograph Sets,
O. Radiano, Y. Graber, M. Mahler, L. Sigal and A. Shamir,
Computer Graphics Forum, Volume 36, 2017. | |
Heterogeneous Knowledge Transfer in Video Emotion Recognition, Attribution and Summarization
B. Xu, Y. Fu, Y.-G. Jiang, B. Li and L. Sigal,
IEEE Transactions on Affective Computing (TAC), 2016. | |
Cross-Domain Matching with Squared-Loss Mutual Information,
M. Yamada, L. Sigal, M. Raptis, M. Toyoda, Y. Chang and M. Sugiyama,
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2015. | |
A Perceptual Control Space for Garment Simulation,
L. Sigal, M. Mahler, S. Diaz, K. McIntosh, E. Carter, T. Richards and J. Hodgins,
ACM Transactions on Graphics (Proc. SIGGRAPH), 2015. | |
Domain Adaptation for Structured Regression,
M. Yamada, Y. Chang and L. Sigal,
International Journal of Computer Vision (IJCV), Special Issue on Domain Adaptation for Vision Applications, 2014. (to appear) | |
High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso,
M. Yamada, W. Jitkrittum, L. Sigal, E. P. Xing and M. Sugiyama,
Neural Computation (NC), 26(1):185-207, 2014. | |
Covariate Shift Adaptation for Discriminative 3D Pose Estimation,
M. Yamada, L. Sigal and M. Raptis,
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2013. (to appear) | |
Dynamical Simulation Priors for Human Motion Tracking,
M. Vondrak, L. Sigal and O. C. Jenkins,
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 35(1):52-65, 2013. | |
Canonical Locality Preserving Latent Variable Model for Discriminative Pose Inference,
Y. Tian, L. Sigal, F. De la Torre and Y. Jia,
Image and Vision Computing (IVC), 31(3):223-230, 2013. | |
Video-based 3D Motion Capture through Biped Control,
M. Vondrak, L. Sigal, J. K. Hodgins and Odest Jenkins,
ACM Transactions on Graphics (Proc. SIGGRAPH), 2012. | |
Human attributes from 3D pose tracking,
M. Livne, L. Sigal, N. Troje and D. Fleet,
Computer Vision and Image Understanding (CVIU), 116:648-660, 2012. | |
Shared kernel information embedding for discriminative inference,
R. Memisevic, L. Sigal and D. Fleet,
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 34(4):778-790, 2012. | |
Loose-limbed People: Estimating Human Pose and Motion using Non-parametric Belief Propagation,
L. Sigal, M. Isard, H. Haussecker and M. J. Black,
International Journal of Computer Vision (IJCV), 98(1):15-48, 2012. | |
Motion Capture from Body-Mounted Cameras,
T. Shiratori, H. S. Park, L. Sigal, Y. Sheikh and J. K. Hodgins,
ACM Transactions on Graphics (Proc. SIGGRAPH), July 2011. (to appear) | |
Stable Spaces for Real-time Clothing,
E. de Aguiar, L. Sigal, A. Treuille and J. K. Hodgins,
ACM Trans. Graphics (Proc. SIGGRAPH), July 2010. | |
HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion,
L. Sigal, A. Balan and M. J. Black,
International Journal of Computer Vision (IJCV), Special Issue on Evaluation of Articulated Human Motion and Pose Estimation, 2010. | |
Skin Color-Based Video Segmentation under Time-Varying Illumination,
L. Sigal, S. Sclaroff and V. Athitsos,
IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(7), pp. 862-877, July 2004. |
Conference Publications
CVPR'24 | |
CVPR'24 | |
CVPR'24 | |
Canadian AI'24 | |
ICASSP'24 | |
WACV'24 | |
WACV'24 | |
NeurIPS'23 | |
BMVC'23 | |
ICCV'23 | |
CGI'23 | |
ICME'23 | |
CVPR'23 | |
CVPR'23 | |
CVPR'23 | |
Eurographics'23 | |
ICLR'23 | |
WACV'22 | |
NeurIPS'22 | |
ECCV'22
Oral | |
ECCV'22
Oral | |
CVPR'22
Oral
Best Paper Finalist | |
Semi-supervised Grounding Alignment for Multimodal Feature Learning,
S.-H. Chou, Z. Fan, J. Little and L. Sigal,
Conference on Robots and Vision (CRV), 2022. | |
TriBERT: Human-centric Audio-visual Representation Learning,
T. Rahman, M. Yang and L. Sigal,
Neural Information Processing Systems (NeurIPS), 2021. | |
Referring Transformer: A One-step Approach to Multi-task Visual Grounding,
M. Li and L. Sigal,
Neural Information Processing Systems (NeurIPS), 2021. | |
A Simple Baseline for Weakly-Supervised Human-centric Relation Detection,
R. Goyal and L. Sigal,
British Machine Vision Conference (BMVC), 2021. | |
Segmentation-grounded Scene Graph Generation,
S. Khandelwal*, M. Suhail* and L. Sigal,
IEEE/CVF International Conference on Computer Vision (ICCV), 2021. | |
PROVIDE: A Probabilistic Framework for Unsupervised Video Decomposition,
P. Zablotskaia, E. Dominici, L. Sigal and A. M. Lehrmann,
Conference on Uncertainty in Artificial Intelligence (UAI), 2021. | |
Weakly-supervised Audio-visual Sound Source Detection and Separation,
T. Rahman and L. Sigal,
IEEE International Conference on Multimedia and Expo (ICME), 2021. | |
Energy-based Learning for Scene Graph Generation,
M. Suhail, A. Mittal, B. Siddiquie, C. Broaddus, J. Eledath, G. Medioni and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. | |
UniT: Unified Knowledge Transfer for Any-shot Object Detection and Segmentation,
S. Khandelwal, R. Goyal and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. | |
Saliency-Guided Image Translation,
L. Jiang, M. Xu, X. Wang and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. | |
APerson-in-Context Synthesis With Compositional Structural Space,
W. Yin, Z. Liu and L. Sigal,
IEEE Winter Conference on Applications of Computer Vision (WACV), 2021. | |
Attribute-guided Image Generation from Layout,
K. Ma, B. Zhao and L. Sigal,
British Machine Vision Conference (BMVC), 2020. | |
Generating Videos of Zero-Shot Compositions of Actions and Objects,
M. Nawhal, M. Zhai, A. Lehrmann, L. Sigal and G. Mori,
European Conference on Computer Vision (ECCV), 2020. | |
Improved Few-Shot Visual Classification,
P. Bateni, R. Goyal, V. Masrani, F. Wood and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. | |
Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction,
Y. Yao, N. Schertler, E. Rosales, H. Rhodin, L. Sigal and A. Sheffer,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. | |
Mixture-Kernel Graph Attention Network for Situation Recognition,
M. Suhail and L. Sigal,
IEEE/CVF International Conference on Computer Vision (ICCV), 2019. | |
Watch, Listen and Tell: Multi-modal Weakly Supervised Dense Event Captioning,
T. Rahman, B. Xu and L. Sigal,
IEEE/CVF International Conference on Computer Vision (ICCV), 2019. | |
AttentionRNN: A Structured Spatial Attention Mechanism,
S. Khandelwal and L. Sigal,
IEEE/CVF International Conference on Computer Vision (ICCV), 2019. | |
GraphGROUND: Graph-based Language Grounding,
M. Bajaj, L. Wang and L. Sigal,
IEEE/CVF International Conference on Computer Vision (ICCV), 2019. | |
LayoutVAE: Stochastic Scene Layout Generation From a Label Set,
A. A. Jyothi, T. Durand, J. He, L. Sigal and G. Mori,
IEEE/CVF International Conference on Computer Vision (ICCV), 2019. | |
DwNet: Dense warp-based network for pose-guided human video generation,
P. Zablotskaia, A. Siarohin, B. Zhao and L. Sigal,
British Machine Vision Conference (BMVC), 2019. | |
Spatio-temporal Relational Reasoning for Video Question Answering,
G. Singh, L. Sigal and J. Little,
British Machine Vision Conference (BMVC), 2019. | |
Image Generation From Layout,
B. Zhao, L. Meng, W. Yin and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. | |
A Variational Auto-Encoder Model for Stochastic Point Processes,
N. Mehrasa, A. A. Jyothi, T. Durand, J. He, L. Sigal and G. Mori,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. | |
Neural Sequential Phrase Grounding (SeqGROUND),
P. Dogan, L. Sigal and M. Gross,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. | |
Weakly-Supervised Spatial Context Networks,
Z. Wu, L. Davis and L. Sigal,
Winter Conference on Applications of Computer Vision (WACV), 2019. | |
Joint Event Detection and Description in Continuous Video Streams,
H. Xu, B. Li, V. Ramanishka, L. Sigal and K. Saenko,
Winter Conference on Applications of Computer Vision (WACV), 2019. | |
Multilevel Language and Vision Integration for Text-to-Clip Retrieval,
H. Xu, K. He, B. Plummer, L. Sigal, S. Sclaroff and K. Saenko,
AAAI Conference on Artificial Intelligence (AAAI), 2019. | |
Middle-Out Decoding,
S. Mehri and L. Sigal,
Neural Information Processing Systems (NeurIPS), 2018. | |
Modular Generative Adversarial Networks,
B. Zhao, B. Chang, Z. Jie and L. Sigal,
European Conference on Computer Vision (ECCV), 2018. | |
Probabilistic Video Generation using Holistic Attribute Control,
J. He, A. Lehrmann, J. Marino, G. Mori and L. Sigal,
European Conference on Computer Vision (ECCV), 2018. | |
A Neural Multi-sequence Alignment TeCHnique (NeuMATCH),
P. Dogan, B. Li, L. Sigal and M. Gross,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. | |
Show Me a Story: Towards Coherent Neural Story Illustration,
H. Ravi, L. Wang, C Muniz, L. Sigal, D. Metaxas and M. Kapadia,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. | |
Story Albums: Creating Fictional Stories from Personal Photograph Sets,
O. Radiano, Y. Graber, M. Mahler, L. Sigal and A. Shamir,
Computer Graphics Forum, Volume 36, 2017. (accepted) | |
Non-parametric Structured Outputs Networks,
A. Lehrmann and L. Sigal,
Neural Information Processing Systems (NIPS), 2017. | |
Visual Reference Resolution using Attention Memory for Visual Dialog,
P. H. Seo, A. Lehrmann, B. Han and L. Sigal,
Neural Information Processing Systems (NIPS), 2017. | |
Weakly-supervised Visual Grounding of Phrases with Linguistic Structures,
F. Xiao, L. Sigal and Y. J. Lee,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. | |
Learn How to Choose: Independent Detectors versus Composite Visual Phrases,
G. Rozenthal, A. Shamir and L. Sigal,
Winter Conference on Applications of Computer Vision (WACV), 2017. | |
Real-time Physics-based Motion Capture with Sparse Sensors,
S. Andrews, I. Huerta, T. Komura, L. Sigal and K. Mitchell,
European Conference on Visual Media Production (CVMP), 2016. | |
Learning Language-Visual Embedding for Movie Understanding with Natural-Languag$
A. Torabi, N. Tandon and L. Sigal,
arXiv:1609.081241, 2016. | |
Semi-supervised Vocabulary-informed Learning,
Y. Fu and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. | |
Learning Activity Progression in LSTMs for Activity Detection and Early Detection,
S. Ma, L. Sigal and S. Sclaroff,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. | |
Harnessing Object and Scene Semantics for Large-Scale Video Understanding,
Z. Wu, Y. Fu, Y.-G. Jiang and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. | |
Video Emotion Recognition with Transferred Deep Feature Encodings,
B. Xu, Y. Fu, Y.-G. Jiang, B. Li and L. Sigal,
ACM International Conference in Multimedia Retrieval (ICMR), 2016. | |
Knowledge Transfer with Interactive Learning of Semantics Relationships,
J. Choi, S. Hwang, L. Sigal and L. Davis,
AAAI Conference on Artificial Intelligence (AAAI), 2016. | |
Exploiting View-Specific Appearance Similarities Across Classes for Zero-shot Pose Prediction: A Metric Learning,
A. Kuznetsova, S. Hwang, B. Rosenhahn and L. Sigal,
AAAI Conference on Artificial Intelligence (AAAI), 2016. | |
Learning to Generate Posters of Scientific Papers,
Y. Qiang, Y. Fu, Y. Guo, Z.-H. Zhou and L. Sigal,
AAAI Conference on Artificial Intelligence (AAAI), 2016. | |
Storyline Representation of Egocentric Videos with an Application to Story-based Search,
B. Xiong, G. Kim and L. Sigal,
IEEE International Conference on Computer Vision (ICCV), 2015. | |
Learning from Synthetic Data Using a Stacked Multichannel Autoencoder,
X. Zhang, Y. Fu, S. Jiang, L. Sigal and G. Agam,
IEEE International Conference on Machine Learning and Applications (ICMLA), 2015. | |
Discovering Collective Narratives of Theme Parks from Large Collections of $
G. Kim and L. Sigal,
KDD 2015 (Practice). | |
Hierarchical Maximum-Margin Clustering,
G.-T. Zhou, S. Hwang, M. Schmidt, L. Sigal and G. Mori,
arXiv:1502.01827, 2015. | |
Joint Photo Stream and Blog Post Summarization and Exploration,
G. Kim, S. Moon, L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. | |
Ranking and Retrival of Image Sequences from Multiple Paragraph Queries,
G. Kim, S. Moon, L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. | |
Space-Time Tree Ensemble for Action Recognition
S. Ma, L. Sigal, S. Sclaroff,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. | |
Expanding Object Detector's Horizon: Incremental Learning Framework for Object Detection in Videos,
A. Kuznetsova, S.-J. Hwang, B. Rosenhahn, L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. | |
Learning to Select and Order Vacation Photographs,
F. Sadeghi, J. R. Tena, A. Farhadi, L. Sigal,
IEEE Winter Conference on Applications of Computer Vision (WACV), 2015. | |
Best Paper Award |
Family Member Identification from Photo Collections,
Q. Dai, P. Carr, L. Sigal, D. Hoiem,
IEEE Winter Conference on Applications of Computer Vision (WACV), 2015. |
A Unified Semantic Embedding: Relating Taxonomies and Attributes,
S.-J. Hwang, L. Sigal,
Neural Information Processing Systems (NIPS), 2014. | |
Parameterizing Object Detectors in the Continuous Pose Space,
K. He, L. Sigal, S. Sclaroff,
European Conference on Computer Vision (ECCV), 2014. | |
Nonparametric Clustering with Distance Dependent Hierarchies,
S. Ghosh, M. Raptis, L. Sigal, E. Sudderth,
Conference on Uncertainty in Artificial Intelligence (UAI), 2014. | |
Joint Summarization of Large-scale Collections of Web Images and Videos for Storyline Reconstruction,
G. Kim, L. Sigal, E. P. Xing,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. | |
Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization,
N. Shapovalova, M. Raptis, L. Sigal, G. Mori,
Neural Information Processing Systems (NIPS), 2013. | |
From Subcategories to Visual Composites: A Multi-Level Framework for Object Detection,
T. Lan, M. Raptis, L. Sigal, G. Mori,
IEEE International Conference on Computer Vision (ICCV), 2013. | |
Poselet Key-framing: A Model for Human Activity Recognition,
M. Raptis, L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013. | |
No Bias Left Behind: Covariate Shift Adaptation for Discriminative 3D Pose Estimation,
M. Yamada, L. Sigal, M. Raptis,
European Conference on Computer Vision (ECCV), 2012. | |
Multi-linear Data-Driven Dynamic Hair Model with Efficient Hair-Body Collision Handling,
P. Guan, L. Sigal, V. Reznitskaya, J. K. Hodgins,
ACM/Eurographics Symposium on Computer Animation (SCA), 2012. | |
Best Paper Award |
Human Context: Modeling human-human interactions for monocular 3D pose estimation,
M. Andriluka and L. Sigal,
VII Conference on Articulated Motion and Deformable Objects (AMDO), 2012. |
Social Roles in Hierarchical Models for Human Activity Recognition,
T. Lan, L. Sigal and G. Mori,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012. | |
Recognizing Character-directed Utterances in Multi-child Interactions,
H. Hajishirzi, J. Lehman, K. Kumatani, L. Sigal, and J. Hodgins,
late-breaking report section of Human Robot Interaction (HRI), 2012. | |
Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines,
M. Zeiler, G. Taylor, L. Sigal, I. Matthews and R. Fergus,
Neural Information Processing Systems (NIPS), 2011. | |
Inferring 3D Body Pose Using Variational Semi-parametric Regression,
Y. Tian, Y. Jia, Y. Shi, Y. Liu, J. Hao and L. Sigal,
IEEE International Conference on Image Processing (ICIP), 2011. | |
Latent Gaussian Mixture Regression for Human Pose Estimation,
Y. Tian, L. Sigal, H. Badino, F. De la Torre and Y. Liu,
Asian Conference on Computer Vision (ACCV), 2010. | |
Human Attributes from 3D Pose Tracking,
L. Sigal, D. Fleet, N. Troje, M. Livne, European Conference on Computer Vision, ECCV 2010. | |
Dynamical Binary Latent Variable Models for 3D Human Pose Tracking,
G. Taylor, L. Sigal, D. Fleet, G. Hinton, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2010. | |
Estimating Contact Dynamics,
M. Brubaker, L. Sigal, D. Fleet, IEEE International Conference on Computer Vision, ICCV 2009. | |
Shared Kernel Information Embedding for Discriminative Inference,
L. Sigal, R. Memisevic, D. Fleet, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009. | |
Physical Simulation for Probabilistic Motion Tracking,
M. Vondrak, L. Sigal and O. C. Jenkins, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008. | |
Combined discriminative and generative articulated pose and non-rigid shape estimation,
L. Sigal, A. Balan and M. J. Black,
Neural Information Processing Systems Conference, NIPS 2007. | |
Shining a Light on Human Pose: On Shadows, Shading and the Estimation of Pose and Shape,
A. Balan, M. J. Black, H. Haussecker and L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition, ICCV 2007. | |
Detailed Human Shape and Pose from Images,
A. Balan, L. Sigal, M. J. Black, J. Davis and H. Haussecker,
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007. | |
Best Paper Award |
Predicting 3D People from 2D Pictures,
L. Sigal and M. J. Black,
IV Conference on Articulated Motion and Deformable Objects, AMDO 2006. |
Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation,
L. Sigal and M. J. Black,
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2006. | |
Tracking Loose-limbed People,
L. Sigal, S. Bhatia, S. Roth, M. J. Black and M. Isard,
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2004. | |
Gibbs Likelihoods for Bayesian Tracking,
S. Roth, L. Sigal and M. J. Black,
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2004. | |
Attractive people: Assembling loose-limbed models using non-parametric belief propagation,
L. Sigal, M. Isard, B. H. Sigelman and M. J. Black,
Advances in Neural Information Processing Systems 16, NIPS 2003. | |
Implicit probabilistic models of human motion for synthesis and tracking,
H. Sidenbladh, M. J. Black and L. Sigal,
European Conference on Computer Vision, ECCV 2002, Springer-Verlag LNCS 2353, Vol. 1, pp. 784-800. | |
3D Hand Pose Reconstruction Using Specialized Mappings,
R. Rosales, V. Athitsos, L. Sigal and S. Sclaroff,
International Conference on Computer Vision, ICCV 2001. | |
Estimation and Prediction of Evolving Color Distributions for Skin Segmentation Under Varying Illumination,
L. Sigal, S. Sclaroff and V. Athitsos,
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000. |
Workshop Publications
Interpretable spatio-temporal attention for video action recognition,
L. Meng, B. Zhao, B. Chang, G. Huang, W. Sun, F. Tung and L. Sigal,
First International Workshop on Holistic Video Understanding (at ICCV), 2019. | |
Informed priors for deep representation learning,
J. Butepage, J. He, C. Zhang, L. Sigal and S. Mandt,
Symposium on Advances in Approximate Bayesian Inference, 2018. | |
Destination Flow for Crowd Simulation,
S. Pellegrini, J. Gall, L. Sigal, L. van Gool,
Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams (ARTEMIS'12), 2012. | |
A Quantitative Evaluation of Video-based 3D Person Tracking,
A. Balan, L. Sigal and M. J. Black,
IEEE Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS 2005. | |
Tracking Complex Objects using Graphical Object Models,
L. Sigal, Y. Zhu, D. Comaniciu and M. J. Black,
1st International Workshop on Complex Motion, Springer-Verlag LNCS 3417, pp. 227-238, 2004. | |
3D Human Limb Detection using Space Carving and Multi-view Eigen Models,
S. Bhatia, L. Sigal, M. Isard and M. J. Black,
IEEE Workshop on Articulated and Nonrigid Motion, 2004. |
Technical Reports
HumanEva: Synchronized Video and Motion Capture Dataset for Evaluation of Articulated Human Motion,
L. Sigal and M. J. Black,
Techniacl Report CS-06-08, Brown University, 2006. |
Refereed Abstracts
Hierarchical Approach for Articulated 3D Pose-Estimation and Tracking (extended abstract),
L. Sigal and M. J. Black,
Learning, Representation and Context for Human Sensing in Video Workshop (in conjunction with CVPR), 2006. |
Patents
Motion Capture from Body Mounted Cameras ,
T. Shiratori, H. S. Park, L. Sigal, Y. Sheikh and J.K. Hodgins, | |
Elastometric Input Device ,
P. Jackson, I. Poupyrev, D. Leithinger and L. Sigal, | |
Stable spaces for rendering character garments in real-time ,
E. de Aguiar, L. Sigal, A. Treuille, J. K. Hodgins, | |
Method and Apparatus for Estimating Body Shape ,
M. J. Black, A. Balan, A. Weiss, L. Sigal, M. Loper, T. St Clair, | |
Graphical Object Models for Detection and Tracking,
L. Sigal, Y. Zhu and D. Comaniciu, | |
Method and System for Aligning Geometric Object Models with Images,
I. Bachelder, L. Jacobson, J. Negro and L. Sigal,
US Pat. 6,804,416, October 2004. |