Burschka, D.[Darius]
* 2002: Scene classification from dense disparity maps in indoor environments
* 2003: Advances in Computational Stereo
* 2003: VICs: A Modular Vision-Based HCI Framework
* 2004: Gesture Recognition Using 3D Appearance and Motion Features
* 2004: Real-time 3D Surface Tracking and Its Applications
* 2004: VICs: A modular HCI framework using spatiotemporal dynamics
* 2008: Collaborative exploration with dynamically configurable sensing agents
* 2008: Direct Pose Estimation with a Monocular Camera
* 2008: geometrically inspired approach to active view planning, A
* 2008: Practical Paradigm and Platform for Video-Based Human-Computer Interaction, A
* 2009: Calibration and registration framework for 3D reconstruction of the Kirche Seefeld
* 2009: Self-Referenced DLR 3D-Modeler, The
* 2009: Stochastic Optimization for Rigid Point Set Registration
* 2010: Adaptive and Generic Corner Detection Based on the Accelerated Segment Test
* 2010: Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes, An
* 2010: Epipolar-Based Stereo Tracking Without Explicit 3D Reconstruction
* 2010: Fast Recovery of Weakly Textured Surfaces from Monocular Image Sequences
* 2010: Towards On-line Intensity-based Surface Recovery from Monocular Images
* 2011: Stochastic global optimization for robust point set registration
* 2015: Dense and Deformable Motion Extraction in Dynamic Scenes Based on Hierarchical MRF Optimization in RGB-D Images
* 2015: Textured/textureless object recognition and pose estimation using RGB-D image
* 2016: Effectiveness of Grasp Attributes and Motion-Constraints for Fine-Grained Recognition of Object Manipulation Actions
* 2016: Motion Estimated-Compensated Reconstruction with Preserved-Features in Free-Breathing Cardiac MRI
* 2017: Reactive Obstacle Avoidance for Highly Maneuverable Vehicles Based on a Two-Stage Optical Flow Clustering
* 2018: Isotropic Reconstruction of MR Images Using 3D Patch-Based Self-Similarity Learning
* 2021: Visual Prediction of Driver Behavior in Shared Road Areas
* 2022: Joint prediction of monocular depth and structure using planar and parallax geometry
* 2022: Skeletal Human Action Recognition using Hybrid Attention based Graph Convolutional Network
Includes: Burschka, D.[Darius] Burschka, D.
28 for Burschka, D.
Burshtynska, K.
* 2016: Monitoring Of The Riverbeds Of Rivers Dniester And Tisza Of The Carpathian Region
* 2023: Hydrological Modeling for Determining Flooded Land from Unmanned Aerial Vehicle Images: Case Study at the Dniester River
Includes: Burshtynska, K. Burshtynska, K.[Khrystyna]
Bursic, S.[Sathya]
* 2021: Quantitative Evaluation Framework of Video De-Identification Methods, A
* 2022: DeepFakes Have No Heart: A Simple rPPG-Based Method to Reveal Fake Videos
Burslem, D.F.R.P.[David F. R. P.]
* 2021: Drivers of Bornean Orangutan Distribution across a Multiple-Use Tropical Landscape
Burson, B.[Byron]
* 2019: Quantification of Soil Organic Carbon in Biochar-Amended Soil Using Ground Penetrating Radar (GPR)
Burson, N.[Nancy]
* 1981: Method and apparatus for producing an image of a person's face at a different age
Burstall, R.M.
* 1976: Subgraph Isomorphism, Matching Relational Structures and Maximal Cliques
* 1977: Some Techniques for Recognizing Structures in Pictures
Burstein, D.
* 2011: Segmentation of textured cell images based on frequency analysis
Burstein, P.D.[Pablo D.]
* 2006: 3D Mouse Brain Reconstruction from Histology Using a Coarse-to-Fine Approach
Burston, R.
* 2014: Effect of Grid Boundary Expansion to Include One Additional Data Source on Ionospheric Imaging Accuracy
* 2018: Analysis of the Regional Ionosphere at Low Latitudes in Support of the Biomass ESA Mission
Bursuc, A.[Andrei]
* 2012: OVIDIUS: A Web Platform for Video Browsing and Search
* 2012: Retrieval of Multiple Instances of Objects in Videos
* 2013: Smartphone-Based Obstacle Detection and Classification System for Assisting Visually Impaired People, A
* 2014: Orientation Covariant Aggregation of Local Descriptors with Embeddings
* 2015: Rotation and translation covariant match kernels for image retrieval
* 2019: Boosting Few-Shot Visual Learning With Self-Supervision
* 2019: Dense Classification and Implanting for Few-Shot Learning
* 2019: Understanding and Improving Kernel Local Descriptors
* 2020: Learning Representations by Predicting Bags of Visual Words
* 2020: Tradi: Tracking Deep Neural Network Weight Distributions
* 2021: OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning
* 2021: Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation
* 2022: Active Learning Strategies for Weakly-Supervised Object Detection
* 2022: Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-Modal Distillation
* 2022: Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data
* 2022: Latent Discriminant Deterministic Uncertainty
* 2022: What to Hide from Your Students: Attention-Guided Masked Image Modeling
* 2023: PØDA: Prompt-driven Zero-shot Domain Adaptation
* 2023: RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving
* 2023: Robust Semantic Segmentation UNCV2023 Challenge Results, The
* 2024: Encoding the Latent Posterior of Bayesian Neural Networks for Uncertainty Quantification
* 2024: Learning to generate training datasets for robust semantic segmentation
Includes: Bursuc, A.[Andrei] Bursuc, A.
22 for Bursuc, A.