Gehlen, S.
* 2005: Strategies and Benefits of Fusion of 2D and 3D Face Recognition
Gehler, P.[Peter]
* 2010: Scene Carving: Scene Consistent Image Retargeting
* 2012: 3D2PM: 3D Deformable Part Models
* 2012: Teaching 3D geometry to deformable part models
* 2013: Occlusion Patterns for Object Class Detection
* 2013: Poselet Conditioned Pictorial Structures
* 2013: Strong Appearance and Expressive Spatial Models for Human Pose Estimation
* 2014: 2D Human Pose Estimation: New Benchmark and State of the Art Analysis
* 2015: Multi-View and 3D Deformable Part Models
* 2016: DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
* 2018: Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation
* 2019: Learning an Event Sequence Embedding for Dense Event-Based Deep Stereo
* 2020: Providing a Single Ground-Truth for Illuminant Estimation for the ColorChecker Dataset
* 2021: CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations
* 2022: Towards Total Recall in Industrial Anomaly Detection
* 2023: TeST: Test-time Self-Training under Distribution Shift
Includes: Gehler, P.[Peter] Gehler, P.
15 for Gehler, P.
Gehler, P.V.[Peter Vincent]
* 2008: Bayesian color constancy revisited
* 2009: Let the kernel figure it out; Principled learning of pre-processing for kernel classifiers
* 2009: On Feature Combination for Multiclass Object Classification
* 2010: On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation
* 2011: Branch&Rank: Non-Linear Object Detection
* 2012: Pottics: The Potts Topic Model for Semantic Image Segmentation
* 2013: Non-parametric Bayesian Network Prior of Human Pose, A
* 2014: Branch&Rank for Efficient Object Detection
* 2014: Efficient Nonlinear Markov Models for Human Motion
* 2014: Human Pose Estimation with Fields of Parts
* 2014: Intrinsic Video
* 2015: 3D object class detection in the wild
* 2015: Efficient Facade Segmentation Using Auto-context
* 2015: informed sampler: A discriminative approach to Bayesian inference in generative computer vision models, The
* 2016: Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
* 2016: Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks
* 2016: Superpixel Convolutional Networks Using Bilateral Inceptions
* 2017: Generative Model of People in Clothing, A
* 2017: Learning to Filter Object Detections
* 2017: Reflectance Adaptive Filtering Improves Intrinsic Image Estimation
* 2017: Semantic Video CNNs Through Representation Warping
* 2017: Unite the People: Closing the Loop Between 3D and 2D Human Representations
* 2017: Video Propagation Networks
* 2018: Deep Directional Statistics: Pose Estimation with Uncertainty Quantification
* 2018: Efficient 2D and 3D Facade Segmentation Using Auto-Context
* 2019: Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice
Includes: Gehler, P.V.[Peter Vincent] Gehler, P.V.[Peter V.] Gehler, P.V.
26 for Gehler, P.V.
Gehlert, A.
* 2017: low-complexity metric for the estimation of perceived chrominance sub-sampling errors in screen content images, A
* 2022: Enhancement Layer Coding for Chroma Sub-Sampled Screen Content Video
Includes: Gehlert, A. Gehlert, A.[Alexander]
Gehlhar, R.
* 2021: Model-Based Adaptive Control of Transfemoral Prostheses: Theory, Simulation, and Experiments
Gehlken, E.[Erlend]
* 2020: Virtual Museum takeouts and DIY Exhibitions-Augmented Reality Apps for Scholarship, Citizen Science and Public Engagement
Gehlot, S.[Shiv]
* 2022: Fusion: Fully Unsupervised Test-time Stain Adaptation via Fused Normalization Statistics