Chum, O.
* 2002: Local affine frames for wide-baseline stereo
* 2002: Randomized RANSAC with T(d,d) test
* 2002: Robust Wide Baseline Stereo from Maximally Stable Extremal Regions
* 2003: Joint Orientation of Epipoles
* 2003: Locally Optimized RANSAC
* 2004: Epipolar geometry estimation via RANSAC benefits from the oriented epipolar constraint
* 2004: Randomized RANSAC with Td,d test
* 2004: Robust Wide Baseline Stereo from Maximally Stable Extremal Regions
* 2004: Towards Complete Free-Form Reconstruction of Complex 3D Scenes from an Unordered Set of Uncalibrated Images
* 2005: geometric error for homographies, The
* 2005: Matching with PROSAC: Progressive Sample Consensus
* 2005: Randomized RANSAC with Sequential Probability Ratio Test
* 2005: Two-View Geometry Estimation Unaffected by a Dominant Plane
* 2006: 3D Geometry from Uncalibrated Images
* 2006: Epipolar Geometry from Two Correspondences
* 2006: Geometric Hashing with Local Affine Frames
* 2007: Exemplar Model for Learning Object Classes, An
* 2007: Object retrieval with large vocabularies and fast spatial matching
* 2007: Scalable near identical image and shot detection
* 2007: Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval
* 2008: Lost in quantization: Improving particular object retrieval in large scale image databases
* 2008: Near Duplicate Image Detection: min-Hash and tf-idf Weighting
* 2008: Optimal Randomized RANSAC
* 2009: Efficient representation of local geometry for large scale object retrieval
* 2009: Geometric min-Hashing: Finding a (thick) needle in a haystack
* 2010: Construction of Precise Local Affine Frames
* 2010: Image Matching and Retrieval by Repetitive Patterns
* 2010: Large-Scale Discovery of Spatially Related Images
* 2010: Learning a Fine Vocabulary
* 2010: Planar Affine Rectification from Change of Scale
* 2010: Unsupervised discovery of co-occurrence in sparse high dimensional data
* 2011: Total recall II: Query expansion revisited
* 2012: Fast computation of min-Hash signatures for image collections
* 2012: Fixing the Locally Optimized RANSAC
* 2012: Homography estimation from correspondences of local elliptical features
* 2012: Negative Evidences and Co-occurences in Image Retrieval: The Benefit of PCA and Whitening
* 2013: Approximate models for fast and accurate epipolar geometry estimation
* 2013: Learning Vocabularies over a Fine Quantization
* 2013: USAC: A Universal Framework for Random Sample Consensus
* 2014: Efficient Image Detail Mining
* 2014: Learning Vocabularies over a Fine Quantization
* 2014: Rectification, and Segmentation of Coplanar Repeated Patterns
* 2014: Relevance Assessment for Visual Video Re-ranking
* 2015: Camera Elevation Estimation from a Single Mountain Landscape Photograph
* 2015: From single image query to detailed 3D reconstruction
* 2015: Low Dimensional Explicit Feature Maps
* 2015: Towards visual words to words
* 2016: CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples
* 2016: Coplanar Repeats by Energy Minimization
* 2016: From Dusk Till Dawn: Modeling in the Dark
* 2016: In the Saddle: Chasing fast and repeatable features
* 2017: Asymmetric Feature Maps with Application to Sketch Based Retrieval
* 2017: Efficient Diffusion on Region Manifolds: Recovering Small Objects with Compact CNN Representations
* 2017: Optimizing explicit feature maps on intervals
* 2017: Robust Data Whitening as an Iteratively Re-weighted Least Squares Problem
* 2018: Deep Shape Matching
* 2018: Efficient contour match kernel
* 2018: Fast Spectral Ranking for Similarity Search
* 2018: Hybrid Diffusion: Spectral-Temporal Graph Filtering for Manifold Ranking
* 2018: Local Orthogonal-Group Testing
* 2018: Mining on Manifolds: Metric Learning Without Labels
* 2018: Radially-Distorted Conjugate Translations
* 2018: Rectification from Radially-Distorted Scales
* 2018: Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
* 2018: Unsupervised Object Discovery for Instance Recognition
* 2019: Explicit Spatial Encoding for Deep Local Descriptors
* 2019: Fine-Tuning CNN Image Retrieval with No Human Annotation
* 2019: Graph-based particular object discovery
* 2019: Label Propagation for Deep Semi-Supervised Learning
* 2019: Local Features and Visual Words Emerge in Activations
* 2019: No Fear of the Dark: Image Retrieval Under Varying Illumination Conditions
* 2019: Targeted Mismatch Adversarial Attack: Query With a Flower to Retrieve the Tower
* 2019: Understanding and Improving Kernel Local Descriptors
* 2020: Graph Convolutional Networks for Learning with Few Clean and Many Noisy Labels
* 2020: Learning and Aggregating Deep Local Descriptors for Instance-Level Recognition
* 2020: Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales
* 2020: Saddle: Fast and repeatable features with good coverage
* 2021: Minimal Solvers for Rectifying From Radially-Distorted Conjugate Translations
* 2022: Edge Augmentation for Large-Scale Sketch Recognition without Sketches
* 2022: Object-Guided Day-Night Visual localization in Urban Scenes
* 2023: Dark Side Augmentation: Generating Diverse Night Examples for Metric Learning
* 2023: Towards Universal Image Embeddings: A Large-Scale Dataset and Challenge for Generic Image Representations
Includes: Chum, O. Chum, O.[Ondrej]
82 for Chum, O.
Chumachenko, K.[Kateryna]
* 2020: Incremental Fast Subclass Discriminant Analysis
* 2021: Speed-up and multi-view extensions to subclass discriminant analysis
* 2022: Self-attention fusion for audiovisual emotion recognition with incomplete data
Chumakov, M.P.[Michael P.]
* 2019: Analysis of the effect of ageing, age, and other factors on iris recognition performance using NEXUS scores dataset
Chuman, T.[Tatsuya]
* 2018: On the Security of Block Scrambling-Based EtC Systems against Extended Jigsaw Puzzle Solver Attacks
* 2019: Image Manipulation Specifications on Social Networking Services for Encryption-then-Compression Systems
Chumbley, L.[Lachlan]
* 2022: Integrating High-Resolution Tactile Sensing into Grasp Stability Prediction
Chumchob, N.
* 2013: Vectorial Total Variation-Based Regularization for Variational Image Registration
Chumerin, N.
* 2011: Driving School System: Learning Basic Driving Skills From a Teacher in a Real Car, The
* 2021: Road Anomaly Detection by Partial Image Reconstruction with Segmentation Coupling
* 2022: Identifying Wrongly Predicted Samples: A Method for Active Learning
* 2024: OOD Aware Supervised Contrastive Learning
Includes: Chumerin, N. Chumerin, N.[Nikolay]