Kernel Methods in Computer Vision
Foundations and Trends® in Computer Graphics and Vision
Mining and cropping common objects from images
Proceedings of the international conference on Multimedia
Two-stage localization for image labeling
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Localizing objects while learning their appearance
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Segmenting salient objects from images and videos
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Multi-stage sampling with boosting cascades for pedestrian detection in images and videos
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
From engineering diagrams to engineering models: Visual recognition and applications
Computer-Aided Design
Efficient visual object tracking with online nearest neighbor classifier
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Saliency density maximization for object detection and localization
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
A Numerical Study of the Bottom-Up and Top-Down Inference Processes in And-Or Graphs
International Journal of Computer Vision
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Fast PRISM: Branch and Bound Hough Transform for Object Class Detection
International Journal of Computer Vision
Branch and bound strategies for non-maximal suppression in object detection
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
Recent advances and trends in visual tracking: A review
Neurocomputing
Exploiting context aware category discovery for image labeling
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
Efficient use of geometric constraints for sliding-window object detection in video
ICVS'11 Proceedings of the 8th international conference on Computer vision systems
Discriminative compact pyramids for object and scene recognition
Pattern Recognition
Structured Learning and Prediction in Computer Vision
Foundations and Trends® in Computer Graphics and Vision
Object detection by admissible region search
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Fast sub-window search with square shape
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Weakly Supervised Localization and Learning with Generic Knowledge
International Journal of Computer Vision
An approach to automatic creation of cinemagraphs
Proceedings of the 20th ACM international conference on Multimedia
Proceedings of the 20th ACM international conference on Multimedia
A tool for automatic cinemagraphs
Proceedings of the 20th ACM international conference on Multimedia
Crosstalk cascades for frame-rate pedestrian detection
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Efficient exact inference for 3d indoor scene understanding
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Unsupervised temporal commonality discovery
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Reordering video shots for event classification using bag-of-words models and string kernels
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
A data-driven detection optimization framework
Neurocomputing
Towards automatic object annotations from global image labels
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Local context priors for object proposal generation
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Arbitrary-Shape object localization using adaptive image grids
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Detecting partially occluded objects with an implicit shape model random field
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Exploiting features: locally interleaved sequential alignment for object detection
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Globally optimal consensus set maximization through rotation search
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Real-time salient object detection
Proceedings of the 21st ACM international conference on Multimedia
Selective Search for Object Recognition
International Journal of Computer Vision
Weighted attentional blocks for probabilistic object tracking
The Visual Computer: International Journal of Computer Graphics
Robust subspace discovery via relaxed rank minimization
Neural Computation
Branch&Rank for Efficient Object Detection
International Journal of Computer Vision
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Most successful object recognition systems rely on binary classification, deciding only if an object is present or not, but not providing information on the actual object location. To estimate the object's location, one can take a sliding window approach, but this strongly increases the computational cost because the classifier or similarity function has to be evaluated over a large set of candidate subwindows. In this paper, we propose a simple yet powerful branch and bound scheme that allows efficient maximization of a large class of quality functions over all possible subimages. It converges to a globally optimal solution typically in linear or even sublinear time, in contrast to the quadratic scaling of exhaustive or sliding window search. We show how our method is applicable to different object detection and image retrieval scenarios. The achieved speedup allows the use of classifiers for localization that formerly were considered too slow for this task, such as SVMs with a spatial pyramid kernel or nearest-neighbor classifiers based on the \chi^2 distance. We demonstrate state-of-the-art localization performance of the resulting systems on the UIUC Cars data set, the PASCAL VOC 2006 data set, and in the PASCAL VOC 2007 competition.